diff --git "a/FineTuneSAM_SEG_ECHO.ipynb" "b/FineTuneSAM_SEG_ECHO.ipynb"
--- "a/FineTuneSAM_SEG_ECHO.ipynb"
+++ "b/FineTuneSAM_SEG_ECHO.ipynb"
@@ -1,14 +1,9563 @@
{
"cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "colab_type": "text",
+ "id": "view-in-github"
+ },
+ "source": [
+ "<a href=\"https://colab.research.google.com/github/unreal-kz/Notes/blob/master/FineTuneSAM_SEG_ECHO.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+ ]
+ },
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Collecting environment information...\n",
+ "PyTorch version: 2.1.2+cu121\n",
+ "Is debug build: False\n",
+ "CUDA used to build PyTorch: 12.1\n",
+ "ROCM used to build PyTorch: N/A\n",
+ "\n",
+ "OS: Microsoft Windows 11 Home\n",
+ "GCC version: Could not collect\n",
+ "Clang version: Could not collect\n",
+ "CMake version: Could not collect\n",
+ "Libc version: N/A\n",
+ "\n",
+ "Python version: 3.9.18 (main, Sep 11 2023, 14:09:26) [MSC v.1916 64 bit (AMD64)] (64-bit runtime)\n",
+ "Python platform: Windows-10-10.0.22621-SP0\n",
+ "Is CUDA available: True\n",
+ "CUDA runtime version: 12.3.107\n",
+ "\n",
+ "CUDA_MODULE_LOADING set to: LAZY\n",
+ "GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3080 Ti\n",
+ "Nvidia driver version: 551.23\n",
+ "cuDNN version: C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.3\\bin\\cudnn_ops_train64_8.dll\n",
+ "HIP runtime version: N/A\n",
+ "MIOpen runtime version: N/A\n",
+ "Is XNNPACK available: True\n",
+ "\n",
+ "CPU:\n",
+ "Architecture=9\n",
+ "\n",
+ "\n",
+ "CurrentClockSpeed=3504\n",
+ "\n",
+ "\n",
+ "DeviceID=CPU0\n",
+ "\n",
+ "\n",
+ "Family=207\n",
+ "\n",
+ "\n",
+ "L2CacheSize=4096\n",
+ "\n",
+ "\n",
+ "L2CacheSpeed=\n",
+ "\n",
+ "\n",
+ "Manufacturer=GenuineIntel\n",
+ "\n",
+ "\n",
+ "MaxClockSpeed=3504\n",
+ "\n",
+ "\n",
+ "Name=11th Gen Intel(R) Core(TM) i9-11900KF @ 3.50GHz\n",
+ "\n",
+ "\n",
+ "ProcessorType=3\n",
+ "\n",
+ "\n",
+ "Revision=\n",
+ "\n",
+ "Versions of relevant libraries:\n",
+ "[pip3] numpy==1.26.3\n",
+ "[pip3] torch==2.1.2+cu121\n",
+ "[pip3] torchaudio==2.1.2\n",
+ "[pip3] torchvision==0.16.2\n",
+ "[conda] blas 1.0 mkl \n",
+ "[conda] cudatoolkit 11.3.1 h59b6b97_2 \n",
+ "[conda] mkl 2023.1.0 h6b88ed4_46358 \n",
+ "[conda] mkl-service 2.4.0 py39h2bbff1b_1 \n",
+ "[conda] mkl_fft 1.3.8 py39h2bbff1b_0 \n",
+ "[conda] mkl_random 1.2.4 py39h59b6b97_0 \n",
+ "[conda] numpy 1.26.3 py39h055cbcc_0 \n",
+ "[conda] numpy-base 1.26.3 py39h65a83cf_0 \n",
+ "[conda] pytorch-cuda 12.1 hde6ce7c_5 pytorch\n",
+ "[conda] pytorch-mutex 1.0 cpu pytorch\n",
+ "[conda] torch 2.1.2+cu121 pypi_0 pypi\n",
+ "[conda] torchaudio 2.1.2 py39_cpu pytorch\n",
+ "[conda] torchvision 0.16.2 py39_cpu pytorch\n"
+ ]
+ }
+ ],
+ "source": [
+ "!python -m torch.utils.collect_env"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import torch"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "a=torch.cuda.FloatTensor()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !pip uninstall torch"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "iobAOGDyff7W",
+ "outputId": "b256e5a4-a406-46f5-fd61-0b46f61afc2a"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Requirement already satisfied: accelerate in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (0.27.2)\n",
+ "Requirement already satisfied: numpy>=1.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (1.26.3)\n",
+ "Requirement already satisfied: packaging>=20.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (23.1)\n",
+ "Requirement already satisfied: psutil in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (5.9.0)\n",
+ "Requirement already satisfied: pyyaml in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (6.0.1)\n",
+ "Requirement already satisfied: torch>=1.10.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (2.1.2+cu121)\n",
+ "Requirement already satisfied: huggingface-hub in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (0.20.2)\n",
+ "Requirement already satisfied: safetensors>=0.3.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (0.4.1)\n",
+ "Requirement already satisfied: filelock in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (3.13.1)\n",
+ "Requirement already satisfied: typing-extensions in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (4.9.0)\n",
+ "Requirement already satisfied: sympy in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (1.12)\n",
+ "Requirement already satisfied: networkx in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (3.1)\n",
+ "Requirement already satisfied: jinja2 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (3.1.2)\n",
+ "Requirement already satisfied: fsspec in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (2023.10.0)\n",
+ "Requirement already satisfied: requests in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from huggingface-hub->accelerate) (2.31.0)\n",
+ "Requirement already satisfied: tqdm>=4.42.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from huggingface-hub->accelerate) (4.66.1)\n",
+ "Requirement already satisfied: colorama in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from tqdm>=4.42.1->huggingface-hub->accelerate) (0.4.6)\n",
+ "Requirement already satisfied: MarkupSafe>=2.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.3)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->huggingface-hub->accelerate) (2.0.4)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->huggingface-hub->accelerate) (3.4)\n",
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->huggingface-hub->accelerate) (2.1.0)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->huggingface-hub->accelerate) (2023.11.17)\n",
+ "Requirement already satisfied: mpmath>=0.19 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n",
+ "Requirement already satisfied: transformers in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (4.37.2)\n",
+ "Requirement already satisfied: filelock in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (3.13.1)\n",
+ "Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (0.20.2)\n",
+ "Requirement already satisfied: numpy>=1.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (1.26.3)\n",
+ "Requirement already satisfied: packaging>=20.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (23.1)\n",
+ "Requirement already satisfied: pyyaml>=5.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (6.0.1)\n",
+ "Requirement already satisfied: regex!=2019.12.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (2023.12.25)\n",
+ "Requirement already satisfied: requests in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (2.31.0)\n",
+ "Requirement already satisfied: tokenizers<0.19,>=0.14 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (0.15.0)\n",
+ "Requirement already satisfied: safetensors>=0.4.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (0.4.1)\n",
+ "Requirement already satisfied: tqdm>=4.27 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (4.66.1)\n",
+ "Requirement already satisfied: fsspec>=2023.5.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (2023.10.0)\n",
+ "Requirement already satisfied: typing-extensions>=3.7.4.3 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (4.9.0)\n",
+ "Requirement already satisfied: colorama in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from tqdm>=4.27->transformers) (0.4.6)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->transformers) (2.0.4)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->transformers) (3.4)\n",
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->transformers) (2.1.0)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->transformers) (2023.11.17)\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install -q transformers datasets segments-ai evaluate\n",
+ "!pip install -U accelerate\n",
+ "!pip install -U transformers"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "True\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(torch.backends.cudnn.enabled)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
"metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "True\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(torch.cuda.is_available())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Available CUDA Devices:\n",
+ "Device 0: NVIDIA GeForce RTX 3080 Ti\n",
+ "CUDA_VISIBLE_DEVICES: Not set (All GPUs are visible)\n"
+ ]
+ }
+ ],
+ "source": [
+ "import torch\n",
+ "\n",
+ "# List all available GPUs\n",
+ "if torch.cuda.is_available():\n",
+ " print(\"Available CUDA Devices:\")\n",
+ " for i in range(torch.cuda.device_count()):\n",
+ " print(f\"Device {i}: {torch.cuda.get_device_name(i)}\")\n",
+ "else:\n",
+ " print(\"No CUDA devices are available\")\n",
+ "\n",
+ "# Check CUDA_VISIBLE_DEVICES environment variable\n",
+ "import os\n",
+ "cuda_visible_devices = os.getenv('CUDA_VISIBLE_DEVICES')\n",
+ "print(\"CUDA_VISIBLE_DEVICES:\", cuda_visible_devices if cuda_visible_devices is not None else \"Not set (All GPUs are visible)\")\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 145,
+ "referenced_widgets": [
+ "8d90aa42c48d4172b040253e980b52a9",
+ "79daa4b480e54dcf8856407c85c65f16",
+ "9b760908da26488aa1fb961aacb8f5ef",
+ "287bfe09367f4253a1566b026c36ad74",
+ "a88e4591259a405b9676fc7446e4625f",
+ "632bb774dbac423e86f9ae4d803e080c",
+ "db0dca9600cc4b1181d00ccd31510d16",
+ "37f202b56e8a4b50ad00bf8d82ac3204",
+ "6347558ca6214490a2de105c9c53edfd",
+ "d96edc8b0bb8422abde7dd63edea1c7f",
+ "22bc3403d15649e48934ada0e462a95a",
+ "ec882c565c89456a97652611d7fc4fb0",
+ "e6427564f5694a65890b06dce89c83f6",
+ "251e600b28934e7d8fc7150c1e293912",
+ "86480f72044b4250af1788dee3bbbb11",
+ "8ebfcb2835664461959c24a642bfc16c",
+ "c16da0793fb9493193b6474650fb7510",
+ "033ce4defe4540cb9b251d2ce1c8d80c",
+ "ee9ba91f11bf4527bc9ea5044b5d7469",
+ "79bce1c28005482fabc4eee0d9871ca7",
+ "0b4ac6328e7840e0b04375152e4cff5f",
+ "4df24038fd64437faefd38f087e8d8a6",
+ "c77d147d149a428c9251a086e068f7c0",
+ "eff45d541581479682d9f448746c82a4",
+ "e7a7df4c1862415799c131fea102087b",
+ "8151bdec05a34ea9bca0634b529814ee",
+ "4de89176ac3946ad870e27a40e04b638",
+ "c99eb0c52f6341cca6c14d611b1eae09",
+ "09fd23cf33ab4ea6b9fb25a97b4b371d",
+ "a00c758a1b0b4f3db31d9dbfa7b50f77",
+ "ccddcb21092644a5a2b586be5db09b86",
+ "41dc48fff7054bfd903dc976a0263684"
+ ]
+ },
+ "id": "WT2jsBUffigw",
+ "outputId": "07fe7e41-3c4d-4ba3-a312-3084e8c43a12"
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "babf77d7da6a454996bbc87bbe6b73b0",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from huggingface_hub import notebook_login\n",
+ "\n",
+ "notebook_login()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "rOAmX6BawqdJ",
+ "outputId": "2c4d8c5e-3e2b-4b7b-aa87-9a2005f5aecd"
+ },
+ "outputs": [],
+ "source": [
+ "# # fc54be4c5ea286d6edd6ad27a963a73a91e5ab1b\n",
+ "from segments import SegmentsClient\n",
+ "from getpass import getpass\n",
+ "\n",
+ "api_key = getpass('Enter your API key: ')\n",
+ "segments_client = SegmentsClient(api_key)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 81,
+ "referenced_widgets": [
+ "9cebf22c32cd44748d31bc579a8ae4a2",
+ "9d433d2f08d14da7a8be97c7872ada56",
+ "fff06ddb73604fdfb406a3376446b5f3",
+ "dabf129903e141ebb989ccc2eb540b34",
+ "24aa75f08b12441fa621d6091c6d0582",
+ "cb7dc2eddd9d4661985df4987ffa6d99",
+ "1dcf2e633103438fb18a18e41f6b42d1",
+ "1538b309424147b2ae5f53dc5388ec61",
+ "41fe2c9e1d774ea68a822356f1d97d7a",
+ "b69f3d8e102043058a92d8d34e92298a",
+ "6b82763efb014b8e92b18686886735ad",
+ "07e2dc52f8234edea0d51c172afa3f56",
+ "7814436b11404b0da781358d8359ce67",
+ "90c80bda0558499182c83f530342257e",
+ "d7d51cd892cf415194b987a553d16ba7",
+ "8397c244f58c48a19c95b63c7fe233d7",
+ "6b6ed63656a44dfb82968e9c2bb3824a",
+ "3b5bb13fe66b48b2a8d589deedc2f548",
+ "c1dff6ce7224438997be06a6fb151dd9",
+ "074f947b9af24017823ee319173423c7",
+ "74ebb22ba2794a46a29fb0a5d3dcb105",
+ "05989c1cfad44c8ba3bb5aa1e01afc85"
+ ]
+ },
+ "id": "Fqox12Ctwxtq",
+ "outputId": "7397d109-c45f-4206-a96c-adc878b695a2"
+ },
+ "outputs": [],
+ "source": [
+ "# from segments.huggingface import release2dataset\n",
+ "\n",
+ "# # dataset_identifier = 'label_h/Test_seg'\n",
+ "# dataset_identifier = 'ai_segment/Real_ECHO_Dateset'\n",
+ "# release_name = 'v0.3_full_label' #'v0.1_9_lbls'\n",
+ "\n",
+ "# release = segments_client.get_release(dataset_identifier, release_name)\n",
+ "# hf_dataset = release2dataset(release)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "9eme461pw8QD",
+ "outputId": "207487a3-5d06-4bf6-b004-2c825beab476",
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "# hf_dataset"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 84,
+ "referenced_widgets": [
+ "39bd4e893b5b4424ab6117b4603f2667",
+ "6fdd569fe7e0451f9190a22f6ef2bd71",
+ "fc0904c810f34c9cabb44a0a4f75d791",
+ "e45f6e7eb34f4587bc506a556e20e3f6",
+ "db168606bdb74c06bf6d64785828ea11",
+ "255a99c1b3074f46a92bba2e6affd4af",
+ "f00ce5e6f92f44ca946d3a3680bab9b2",
+ "66175f804f78452898366d5a994f1c3d",
+ "bf9fe521b3094e61b80e76ca7d584e7d",
+ "90d454feb6c547938f90c57076b670a8",
+ "91f025b6a33b42e99f324323f9b07740"
+ ]
+ },
+ "id": "Gq0M2WMbw-Wr",
+ "outputId": "bf76ade7-9992-4080-908e-e2e010d5ec56"
+ },
+ "outputs": [],
+ "source": [
+ "# from segments.utils import get_semantic_bitmap\n",
+ "\n",
+ "\n",
+ "# def convert_segmentation_bitmap(example):\n",
+ "# return {\n",
+ "# \"label.segmentation_bitmap\":\n",
+ "# get_semantic_bitmap(\n",
+ "# example[\"label.segmentation_bitmap\"],\n",
+ "# example[\"label.annotations\"],\n",
+ "# )\n",
+ "# }\n",
+ "\n",
+ "\n",
+ "# semantic_dataset = hf_dataset.map(\n",
+ "# convert_segmentation_bitmap,\n",
+ "# )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {
+ "id": "AZbQ0YZZw_4o"
+ },
+ "outputs": [],
+ "source": [
+ "# semantic_dataset = semantic_dataset.rename_column('image', 'pixel_values')\n",
+ "# semantic_dataset = semantic_dataset.rename_column('label.segmentation_bitmap', 'label')\n",
+ "# semantic_dataset = semantic_dataset.remove_columns(['name', 'uuid', 'status', 'label.annotations'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 113,
+ "referenced_widgets": [
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+ "7887c0594a9644489ac6660ce2cd9adf",
+ "b3020aba141a49f5809b0051783b462e",
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+ "4ca35eafdcb74cd2a69daef85e219d0e",
+ "9db3135bd3e54f03bd7aa3bc5a2db490",
+ "a6f84aa825ff41a6b7019821ffb5922b",
+ "78fddd61995a4c84886421a874c8e6df",
+ "5d49d5d1072c423ea031f432fc2b0305",
+ "12477a5d060a4d42be6405e81099b67e"
+ ]
+ },
+ "id": "DQ7g8yFaxBS4",
+ "outputId": "ef5c9bfe-6814-4495-cd9a-11bfa1387a9e"
+ },
+ "outputs": [],
+ "source": [
+ "hf_dataset_identifier = \"unreal-hug/REAL_DATASET_SEG_401_6_lbls\"\n",
+ "# semantic_dataset.push_to_hub(hf_dataset_identifier)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 177,
+ "referenced_widgets": [
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+ "1fe0124d8b604280ab52f77179d9c13b",
+ "a96d66b43ef849309507e67208884cd3"
+ ]
+ },
+ "id": "_DFh0t9AxLOP",
+ "outputId": "f82100b1-1b06-4902-a10f-6041b793f16e"
+ },
+ "outputs": [],
+ "source": [
+ "from datasets import load_dataset\n",
+ "\n",
+ "ds = load_dataset(hf_dataset_identifier)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {
+ "id": "3YZr1fuhxPgw"
+ },
+ "outputs": [],
+ "source": [
+ "ds = ds.shuffle(seed=1)\n",
+ "ds = ds[\"train\"].train_test_split(test_size=0.2)\n",
+ "train_ds = ds[\"train\"]\n",
+ "test_ds = ds[\"test\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 66,
+ "referenced_widgets": [
+ "9ae07b85926d4542a434bd9e5f0ed62f",
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+ ]
+ },
+ "id": "FdU0XqN5xSae",
+ "outputId": "0d40b716-5a11-4bbc-d455-e6a310fef4f5"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Id2label: {0: 'unlabeled', 1: 'LV', 2: 'RV', 3: 'RA', 4: 'LA', 5: 'VS', 6: 'AS', 7: 'MK', 8: 'TK', 9: 'ASD', 10: 'VSD', 11: 'AK'}\n"
+ ]
+ }
+ ],
+ "source": [
+ "import json\n",
+ "from huggingface_hub import hf_hub_download\n",
+ "\n",
+ "filename = \"id2label.json\"\n",
+ "id2label = json.load(open(hf_hub_download(repo_id=hf_dataset_identifier, filename=filename, repo_type=\"dataset\"), \"r\"))\n",
+ "id2label = {int(k): v for k, v in id2label.items()}\n",
+ "label2id = {v: k for k, v in id2label.items()}\n",
+ "\n",
+ "num_labels = len(id2label)\n",
+ "print(\"Id2label:\", id2label)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 86,
+ "referenced_widgets": [
+ "248f4eeefce349c6826f70434b4a62bd",
+ "d665536d08d2456599c2c199ae6eb963",
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+ "db626e91ae3441c49ce83f64a06e8e8c"
+ ]
+ },
+ "id": "oIOUoYIUxYYp",
+ "outputId": "c22328c5-fd68-4051-81ed-f0d77361523c"
+ },
+ "outputs": [],
+ "source": [
+ "from torchvision.transforms import ColorJitter\n",
+ "from transformers import (\n",
+ " SegformerImageProcessor,\n",
+ ")\n",
+ "\n",
+ "processor = SegformerImageProcessor()\n",
+ "jitter = ColorJitter(brightness=0.25, contrast=0.25, saturation=0.25, hue=0.1)\n",
+ "\n",
+ "def train_transforms(example_batch):\n",
+ " images = [jitter(x) for x in example_batch['pixel_values']]\n",
+ " labels = [x for x in example_batch['label']]\n",
+ " inputs = processor(images, labels)\n",
+ " return inputs\n",
+ "\n",
+ "\n",
+ "def val_transforms(example_batch):\n",
+ " images = [x for x in example_batch['pixel_values']]\n",
+ " labels = [x for x in example_batch['label']]\n",
+ " inputs = processor(images, labels)\n",
+ " return inputs\n",
+ "\n",
+ "\n",
+ "# Set transforms\n",
+ "train_ds.set_transform(train_transforms)\n",
+ "test_ds.set_transform(val_transforms)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 136,
+ "referenced_widgets": [
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+ ]
+ },
+ "id": "kqKDS-8KxaJX",
+ "outputId": "17108fff-c192-4d22-ff6e-fe38abf0e58a"
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "c:\\Users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages\\torch\\_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n",
+ " return self.fget.__get__(instance, owner)()\n",
+ "Some weights of SegformerForSemanticSegmentation were not initialized from the model checkpoint at nvidia/mit-b0 and are newly initialized: ['decode_head.batch_norm.bias', 'decode_head.batch_norm.num_batches_tracked', 'decode_head.batch_norm.running_mean', 'decode_head.batch_norm.running_var', 'decode_head.batch_norm.weight', 'decode_head.classifier.bias', 'decode_head.classifier.weight', 'decode_head.linear_c.0.proj.bias', 'decode_head.linear_c.0.proj.weight', 'decode_head.linear_c.1.proj.bias', 'decode_head.linear_c.1.proj.weight', 'decode_head.linear_c.2.proj.bias', 'decode_head.linear_c.2.proj.weight', 'decode_head.linear_c.3.proj.bias', 'decode_head.linear_c.3.proj.weight', 'decode_head.linear_fuse.weight']\n",
+ "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "SegformerForSemanticSegmentation(\n",
+ " (segformer): SegformerModel(\n",
+ " (encoder): SegformerEncoder(\n",
+ " (patch_embeddings): ModuleList(\n",
+ " (0): SegformerOverlapPatchEmbeddings(\n",
+ " (proj): Conv2d(3, 32, kernel_size=(7, 7), stride=(4, 4), padding=(3, 3))\n",
+ " (layer_norm): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (1): SegformerOverlapPatchEmbeddings(\n",
+ " (proj): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
+ " (layer_norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (2): SegformerOverlapPatchEmbeddings(\n",
+ " (proj): Conv2d(64, 160, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
+ " (layer_norm): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (3): SegformerOverlapPatchEmbeddings(\n",
+ " (proj): Conv2d(160, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
+ " (layer_norm): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " )\n",
+ " (block): ModuleList(\n",
+ " (0): ModuleList(\n",
+ " (0): SegformerLayer(\n",
+ " (layer_norm_1): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+ " (attention): SegformerAttention(\n",
+ " (self): SegformerEfficientSelfAttention(\n",
+ " (query): Linear(in_features=32, out_features=32, bias=True)\n",
+ " (key): Linear(in_features=32, out_features=32, bias=True)\n",
+ " (value): Linear(in_features=32, out_features=32, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " (sr): Conv2d(32, 32, kernel_size=(8, 8), stride=(8, 8))\n",
+ " (layer_norm): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (output): SegformerSelfOutput(\n",
+ " (dense): Linear(in_features=32, out_features=32, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (drop_path): Identity()\n",
+ " (layer_norm_2): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+ " (mlp): SegformerMixFFN(\n",
+ " (dense1): Linear(in_features=32, out_features=128, bias=True)\n",
+ " (dwconv): SegformerDWConv(\n",
+ " (dwconv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128)\n",
+ " )\n",
+ " (intermediate_act_fn): GELUActivation()\n",
+ " (dense2): Linear(in_features=128, out_features=32, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (1): SegformerLayer(\n",
+ " (layer_norm_1): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+ " (attention): SegformerAttention(\n",
+ " (self): SegformerEfficientSelfAttention(\n",
+ " (query): Linear(in_features=32, out_features=32, bias=True)\n",
+ " (key): Linear(in_features=32, out_features=32, bias=True)\n",
+ " (value): Linear(in_features=32, out_features=32, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " (sr): Conv2d(32, 32, kernel_size=(8, 8), stride=(8, 8))\n",
+ " (layer_norm): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (output): SegformerSelfOutput(\n",
+ " (dense): Linear(in_features=32, out_features=32, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (drop_path): SegformerDropPath(p=0.014285714365541935)\n",
+ " (layer_norm_2): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+ " (mlp): SegformerMixFFN(\n",
+ " (dense1): Linear(in_features=32, out_features=128, bias=True)\n",
+ " (dwconv): SegformerDWConv(\n",
+ " (dwconv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128)\n",
+ " )\n",
+ " (intermediate_act_fn): GELUActivation()\n",
+ " (dense2): Linear(in_features=128, out_features=32, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " )\n",
+ " (1): ModuleList(\n",
+ " (0): SegformerLayer(\n",
+ " (layer_norm_1): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+ " (attention): SegformerAttention(\n",
+ " (self): SegformerEfficientSelfAttention(\n",
+ " (query): Linear(in_features=64, out_features=64, bias=True)\n",
+ " (key): Linear(in_features=64, out_features=64, bias=True)\n",
+ " (value): Linear(in_features=64, out_features=64, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " (sr): Conv2d(64, 64, kernel_size=(4, 4), stride=(4, 4))\n",
+ " (layer_norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (output): SegformerSelfOutput(\n",
+ " (dense): Linear(in_features=64, out_features=64, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (drop_path): SegformerDropPath(p=0.02857142873108387)\n",
+ " (layer_norm_2): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+ " (mlp): SegformerMixFFN(\n",
+ " (dense1): Linear(in_features=64, out_features=256, bias=True)\n",
+ " (dwconv): SegformerDWConv(\n",
+ " (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)\n",
+ " )\n",
+ " (intermediate_act_fn): GELUActivation()\n",
+ " (dense2): Linear(in_features=256, out_features=64, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (1): SegformerLayer(\n",
+ " (layer_norm_1): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+ " (attention): SegformerAttention(\n",
+ " (self): SegformerEfficientSelfAttention(\n",
+ " (query): Linear(in_features=64, out_features=64, bias=True)\n",
+ " (key): Linear(in_features=64, out_features=64, bias=True)\n",
+ " (value): Linear(in_features=64, out_features=64, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " (sr): Conv2d(64, 64, kernel_size=(4, 4), stride=(4, 4))\n",
+ " (layer_norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (output): SegformerSelfOutput(\n",
+ " (dense): Linear(in_features=64, out_features=64, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (drop_path): SegformerDropPath(p=0.04285714402794838)\n",
+ " (layer_norm_2): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+ " (mlp): SegformerMixFFN(\n",
+ " (dense1): Linear(in_features=64, out_features=256, bias=True)\n",
+ " (dwconv): SegformerDWConv(\n",
+ " (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)\n",
+ " )\n",
+ " (intermediate_act_fn): GELUActivation()\n",
+ " (dense2): Linear(in_features=256, out_features=64, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " )\n",
+ " (2): ModuleList(\n",
+ " (0): SegformerLayer(\n",
+ " (layer_norm_1): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+ " (attention): SegformerAttention(\n",
+ " (self): SegformerEfficientSelfAttention(\n",
+ " (query): Linear(in_features=160, out_features=160, bias=True)\n",
+ " (key): Linear(in_features=160, out_features=160, bias=True)\n",
+ " (value): Linear(in_features=160, out_features=160, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " (sr): Conv2d(160, 160, kernel_size=(2, 2), stride=(2, 2))\n",
+ " (layer_norm): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (output): SegformerSelfOutput(\n",
+ " (dense): Linear(in_features=160, out_features=160, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (drop_path): SegformerDropPath(p=0.05714285746216774)\n",
+ " (layer_norm_2): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+ " (mlp): SegformerMixFFN(\n",
+ " (dense1): Linear(in_features=160, out_features=640, bias=True)\n",
+ " (dwconv): SegformerDWConv(\n",
+ " (dwconv): Conv2d(640, 640, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=640)\n",
+ " )\n",
+ " (intermediate_act_fn): GELUActivation()\n",
+ " (dense2): Linear(in_features=640, out_features=160, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (1): SegformerLayer(\n",
+ " (layer_norm_1): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+ " (attention): SegformerAttention(\n",
+ " (self): SegformerEfficientSelfAttention(\n",
+ " (query): Linear(in_features=160, out_features=160, bias=True)\n",
+ " (key): Linear(in_features=160, out_features=160, bias=True)\n",
+ " (value): Linear(in_features=160, out_features=160, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " (sr): Conv2d(160, 160, kernel_size=(2, 2), stride=(2, 2))\n",
+ " (layer_norm): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " (output): SegformerSelfOutput(\n",
+ " (dense): Linear(in_features=160, out_features=160, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (drop_path): SegformerDropPath(p=0.0714285746216774)\n",
+ " (layer_norm_2): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+ " (mlp): SegformerMixFFN(\n",
+ " (dense1): Linear(in_features=160, out_features=640, bias=True)\n",
+ " (dwconv): SegformerDWConv(\n",
+ " (dwconv): Conv2d(640, 640, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=640)\n",
+ " )\n",
+ " (intermediate_act_fn): GELUActivation()\n",
+ " (dense2): Linear(in_features=640, out_features=160, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " )\n",
+ " (3): ModuleList(\n",
+ " (0): SegformerLayer(\n",
+ " (layer_norm_1): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+ " (attention): SegformerAttention(\n",
+ " (self): SegformerEfficientSelfAttention(\n",
+ " (query): Linear(in_features=256, out_features=256, bias=True)\n",
+ " (key): Linear(in_features=256, out_features=256, bias=True)\n",
+ " (value): Linear(in_features=256, out_features=256, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " (output): SegformerSelfOutput(\n",
+ " (dense): Linear(in_features=256, out_features=256, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (drop_path): SegformerDropPath(p=0.08571428805589676)\n",
+ " (layer_norm_2): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+ " (mlp): SegformerMixFFN(\n",
+ " (dense1): Linear(in_features=256, out_features=1024, bias=True)\n",
+ " (dwconv): SegformerDWConv(\n",
+ " (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024)\n",
+ " )\n",
+ " (intermediate_act_fn): GELUActivation()\n",
+ " (dense2): Linear(in_features=1024, out_features=256, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (1): SegformerLayer(\n",
+ " (layer_norm_1): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+ " (attention): SegformerAttention(\n",
+ " (self): SegformerEfficientSelfAttention(\n",
+ " (query): Linear(in_features=256, out_features=256, bias=True)\n",
+ " (key): Linear(in_features=256, out_features=256, bias=True)\n",
+ " (value): Linear(in_features=256, out_features=256, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " (output): SegformerSelfOutput(\n",
+ " (dense): Linear(in_features=256, out_features=256, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " (drop_path): SegformerDropPath(p=0.10000000149011612)\n",
+ " (layer_norm_2): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+ " (mlp): SegformerMixFFN(\n",
+ " (dense1): Linear(in_features=256, out_features=1024, bias=True)\n",
+ " (dwconv): SegformerDWConv(\n",
+ " (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024)\n",
+ " )\n",
+ " (intermediate_act_fn): GELUActivation()\n",
+ " (dense2): Linear(in_features=1024, out_features=256, bias=True)\n",
+ " (dropout): Dropout(p=0.0, inplace=False)\n",
+ " )\n",
+ " )\n",
+ " )\n",
+ " )\n",
+ " (layer_norm): ModuleList(\n",
+ " (0): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+ " (1): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+ " (2): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+ " (3): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+ " )\n",
+ " )\n",
+ " )\n",
+ " (decode_head): SegformerDecodeHead(\n",
+ " (linear_c): ModuleList(\n",
+ " (0): SegformerMLP(\n",
+ " (proj): Linear(in_features=32, out_features=256, bias=True)\n",
+ " )\n",
+ " (1): SegformerMLP(\n",
+ " (proj): Linear(in_features=64, out_features=256, bias=True)\n",
+ " )\n",
+ " (2): SegformerMLP(\n",
+ " (proj): Linear(in_features=160, out_features=256, bias=True)\n",
+ " )\n",
+ " (3): SegformerMLP(\n",
+ " (proj): Linear(in_features=256, out_features=256, bias=True)\n",
+ " )\n",
+ " )\n",
+ " (linear_fuse): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
+ " (batch_norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+ " (activation): ReLU()\n",
+ " (dropout): Dropout(p=0.1, inplace=False)\n",
+ " (classifier): Conv2d(256, 12, kernel_size=(1, 1), stride=(1, 1))\n",
+ " )\n",
+ ")"
+ ]
+ },
+ "execution_count": 36,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "from transformers import SegformerForSemanticSegmentation\n",
+ "\n",
+ "pretrained_model_name = \"nvidia/mit-b0\"\n",
+ "model = SegformerForSemanticSegmentation.from_pretrained(\n",
+ " pretrained_model_name,\n",
+ " id2label=id2label,\n",
+ " label2id=label2id\n",
+ ")\n",
+ "\n",
+ "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
+ "model.to(device) # Move your model to the selected device\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {
+ "id": "rgrgU6shxb56"
+ },
+ "outputs": [],
+ "source": [
+ "from transformers import TrainingArguments\n",
+ "\n",
+ "epochs = 25\n",
+ "lr = 0.0001\n",
+ "batch_size = 2\n",
+ "\n",
+ "hub_model_id = \"segformer-b0-finetuned-segments-ECHO-feb-13-v1\"\n",
+ "\n",
+ "training_args = TrainingArguments(\n",
+ " \"segformer-b0-finetuned-segments-outputs\",\n",
+ " learning_rate=lr,\n",
+ " num_train_epochs=epochs,\n",
+ " per_device_train_batch_size=batch_size,\n",
+ " per_device_eval_batch_size=batch_size,\n",
+ " save_total_limit=3,\n",
+ " evaluation_strategy=\"steps\",\n",
+ " save_strategy=\"steps\",\n",
+ " save_steps=20,\n",
+ " eval_steps=20,\n",
+ " logging_steps=1,\n",
+ " eval_accumulation_steps=5,\n",
+ " load_best_model_at_end=True,\n",
+ " push_to_hub=True,\n",
+ " hub_model_id=hub_model_id,\n",
+ "\n",
+ " hub_strategy=\"end\",\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
+ "5ce930f685ec40e596ffe7097c563aaf",
+ "69512d0cbc3a40e688f836833b61af92",
+ "35cfdd432b6840f5b7bf0492376135e2",
+ "017cfb0b0de94adf8b2a67c4c1cbed32",
+ "f054f00917c640f3be2bfcca7e713057",
+ "e3f0794db93f4c00b05e6756f50f7e34",
+ "a1778b25578e4194a075ddec31d852fe",
+ "51568a44ad5644189f24c8ba5e324c4d",
+ "71ca7d48dd1045698bae348ea1f9118b",
+ "8d07d5c05eac47b989c92d02f075f646",
+ "56158227e30e4a00a670e2320864e269"
+ ]
+ },
+ "id": "ekMBkUy5xdFV",
+ "outputId": "9a22db9e-1c89-4821-e99b-66a0ef10585d"
+ },
+ "outputs": [],
+ "source": [
+ "import torch\n",
+ "from torch import nn\n",
+ "import evaluate\n",
+ "import multiprocessing\n",
+ "\n",
+ "metric = evaluate.load(\"mean_iou\")\n",
+ "\n",
+ "def compute_metrics(eval_pred):\n",
+ " with torch.no_grad():\n",
+ " logits, labels = eval_pred\n",
+ " logits_tensor = torch.from_numpy(logits)\n",
+ " # scale the logits to the size of the label\n",
+ " logits_tensor = nn.functional.interpolate(\n",
+ " logits_tensor,\n",
+ " size=labels.shape[-2:],\n",
+ " mode=\"bilinear\",\n",
+ " align_corners=False,\n",
+ " ).argmax(dim=1)\n",
+ "\n",
+ " pred_labels = logits_tensor.detach().cpu().numpy()\n",
+ " metrics = metric._compute(\n",
+ " predictions=pred_labels,\n",
+ " references=labels,\n",
+ " num_labels=len(id2label),\n",
+ " ignore_index=0,\n",
+ " reduce_labels=processor.do_reduce_labels,\n",
+ " )\n",
+ "\n",
+ " # add per category metrics as individual key-value pairs\n",
+ " per_category_accuracy = metrics.pop(\"per_category_accuracy\").tolist()\n",
+ " per_category_iou = metrics.pop(\"per_category_iou\").tolist()\n",
+ "\n",
+ " metrics.update({f\"accuracy_{id2label[i]}\": v for i, v in enumerate(per_category_accuracy)})\n",
+ " metrics.update({f\"iou_{id2label[i]}\": v for i, v in enumerate(per_category_iou)})\n",
+ "\n",
+ " return metrics"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {
+ "id": "NqJfQsGHxqAQ"
+ },
+ "outputs": [],
+ "source": [
+ "from transformers import Trainer\n",
+ "\n",
+ "trainer = Trainer(\n",
+ " model=model,\n",
+ " args=training_args,\n",
+ " train_dataset=train_ds,\n",
+ " eval_dataset=test_ds,\n",
+ " compute_metrics=compute_metrics,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 1000
+ },
+ "id": "eotoZ9TWxrtt",
+ "outputId": "16ad97a9-0aab-4af7-f7c6-4969f1d20d9b"
+ },
+ "outputs": [
+ {
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+ " 0%| | 0/4000 [00:00<?, ?it/s]"
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+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
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+ "{'loss': 1.7534, 'learning_rate': 9.952500000000001e-05, 'epoch': 0.12}\n",
+ "{'loss': 1.8939, 'learning_rate': 9.95e-05, 'epoch': 0.12}\n"
+ ]
+ },
+ {
+ "data": {
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+ "version_major": 2,
+ "version_minor": 0
+ },
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n",
+ "Checkpoint destination directory segformer-b0-finetuned-segments-outputs\\checkpoint-20 already exists and is non-empty.Saving will proceed but saved results may be invalid.\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "{'eval_loss': 1.988379955291748, 'eval_mean_iou': 0.08309316723217665, 'eval_mean_accuracy': 0.12846487983660576, 'eval_overall_accuracy': 0.22557309597328942, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.35013841614934627, 'eval_accuracy_RV': 0.0, 'eval_accuracy_RA': 0.012044741068330199, 'eval_accuracy_LA': 0.35264374755589706, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0021921911085450345, 'eval_accuracy_VSD': 0.12712537859477613, 'eval_accuracy_AK': 0.440504323889163, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.2520954482728996, 'eval_iou_RV': 0.0, 'eval_iou_RA': 0.01194566224390361, 'eval_iou_LA': 0.22483184414294916, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0021799587332914684, 'eval_iou_VSD': 0.08716728181191977, 'eval_iou_AK': 0.3358046443489795, 'eval_runtime': 4.9744, 'eval_samples_per_second': 16.283, 'eval_steps_per_second': 8.242, 'epoch': 0.12}\n",
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+ "{'loss': 1.4798, 'learning_rate': 9.910000000000001e-05, 'epoch': 0.23}\n",
+ "{'loss': 1.4638, 'learning_rate': 9.907500000000001e-05, 'epoch': 0.23}\n",
+ "{'loss': 1.4609, 'learning_rate': 9.905000000000001e-05, 'epoch': 0.24}\n",
+ "{'loss': 1.5565, 'learning_rate': 9.9025e-05, 'epoch': 0.24}\n",
+ "{'loss': 1.4656, 'learning_rate': 9.900000000000001e-05, 'epoch': 0.25}\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "d03ca908e99b4618b2cb076ae0456c64",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ " 0%| | 0/41 [00:00<?, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n",
+ "Checkpoint destination directory segformer-b0-finetuned-segments-outputs\\checkpoint-40 already exists and is non-empty.Saving will proceed but saved results may be invalid.\n"
+ ]
+ },
+ {
+ "name": "stdout",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "text/plain": [
+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "name": "stdout",
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "name": "stdout",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "name": "stdout",
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+ {
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+ "text/plain": [
+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ "metadata": {},
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "name": "stdout",
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ {
+ "name": "stdout",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ {
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+ "version_major": 2,
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+ "text/plain": [
+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "name": "stdout",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "name": "stdout",
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "name": "stdout",
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+ {
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+ "text/plain": [
+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " 0%| | 0/41 [00:00<?, ?it/s]"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ " iou = total_area_intersect / total_area_union\n",
+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+ " acc = total_area_intersect / total_area_label\n"
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+ "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
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+ "outputId": "f80a6791-acb6-4888-ef6b-d6808cabdcd1"
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+ "outputs": [],
+ "source": [
+ "kwargs = {\n",
+ " \"tags\": [\"vision\", \"image-segmentation\"],\n",
+ " \"finetuned_from\": pretrained_model_name,\n",
+ " \"dataset\": hf_dataset_identifier,\n",
+ "}\n",
+ "\n",
+ "processor.push_to_hub(hub_model_id)\n",
+ "trainer.push_to_hub(**kwargs)"
+ ]
+ },
+ {
+ "cell_type": "code",
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+ "metadata": {
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+ "outputId": "587e4e75-4cc6-4ab1-b062-28c1bbd4f369"
+ },
+ "outputs": [],
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+ "from transformers import SegformerImageProcessor, SegformerForSemanticSegmentation\n",
+ "\n",
+ "processor = SegformerImageProcessor.from_pretrained(\"nvidia/segformer-b0-finetuned-ade-512-512\")\n",
+ "model = SegformerForSemanticSegmentation.from_pretrained(f\"unreal-hug/{hub_model_id}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
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