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Browse files- README.md +1 -1
- requirements.txt +3 -2
- run.ipynb +1 -1
README.md
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sdk: gradio
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sdk_version:
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app_file: run.py
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pinned: false
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hf_oauth: true
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sdk: gradio
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sdk_version: 5.0.0
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app_file: run.py
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pinned: false
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hf_oauth: true
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requirements.txt
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gradio-client @ git+https://github.com/gradio-app/gradio@
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https://gradio-pypi-previews.s3.amazonaws.com/
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gradio-client @ git+https://github.com/gradio-app/gradio@bbf9ba7e997022960c621f72baa891185bd03732#subdirectory=client/python
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https://gradio-pypi-previews.s3.amazonaws.com/bbf9ba7e997022960c621f72baa891185bd03732/gradio-5.0.0-py3-none-any.whl
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Pillow
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run.ipynb
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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: sub_block_render"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/sub_block_render/cheetah.jpg\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/sub_block_render/frog.jpg"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "from pathlib import Path\n", "\n", "from PIL import Image\n", "\n", "root = Path(os.path.abspath(''))\n", "\n", "def infer(\n", " text,\n", " guidance_scale,\n", "):\n", "\n", " img = (\n", " Image.open(root / \"cheetah.jpg\")\n", " if text == \"Cheetah\"\n", " else Image.open(root / \"frog.jpg\")\n", " )\n", " img = img.resize((224, 224))\n", "\n", " return ([img, img, img, img], \"image\")\n", "\n", "block = gr.Blocks()\n", "\n", "examples = [\n", " [\"A serious capybara at work, wearing a suit\", 7],\n", " [\"A Squirtle fine dining with a view to the London Eye\", 7],\n", " [\"A tamale food cart in front of a Japanese Castle\", 7],\n", " [\"a graffiti of a robot serving meals to people\", 7],\n", " [\"a beautiful cabin in Attersee, Austria, 3d animation style\", 7],\n", "]\n", "\n", "with block as demo:\n", " with gr.Row(elem_id=\"prompt-container\", equal_height=True):\n", " text = gr.Textbox(\n", " label=\"Enter your prompt\",\n", " show_label=False,\n", " max_lines=1,\n", " placeholder=\"Enter your prompt\",\n", " elem_id=\"prompt-text-input\",\n", " )\n", "\n", " gallery = gr.Gallery(\n", " label=\"Generated images\", show_label=False, elem_id=\"gallery\", rows=2, columns=2\n", " )\n", " out_txt = gr.Textbox(\n", " label=\"Prompt\",\n", " placeholder=\"Enter a prompt to generate an image\",\n", " lines=3,\n", " elem_id=\"prompt-text-input\",\n", " )\n", "\n", " guidance_scale = gr.Slider(\n", " label=\"Guidance Scale\", minimum=0, maximum=50, value=7.5, step=0.1\n", " )\n", "\n", " ex = gr.Examples(\n", " examples=examples,\n", " fn=infer,\n", " inputs=[text, guidance_scale],\n", " outputs=[gallery, out_txt],\n", " cache_examples=True,\n", " )\n", "\n", " text.submit(\n", " infer,\n", " inputs=[text, guidance_scale],\n", " outputs=[gallery, out_txt],\n", " concurrency_id=\"infer\",\n", " concurrency_limit=8,\n", " )\n", "\n", "with gr.Blocks() as demo:\n", " block.render()\n", "\n", "if __name__ == \"__main__\":\n", " demo.queue(max_size=10, api_open=False).launch(show_api=False)\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: sub_block_render"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio Pillow "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/sub_block_render/cheetah.jpg\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/sub_block_render/frog.jpg"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "from pathlib import Path\n", "\n", "from PIL import Image\n", "\n", "root = Path(os.path.abspath(''))\n", "\n", "def infer(\n", " text,\n", " guidance_scale,\n", "):\n", "\n", " img = (\n", " Image.open(root / \"cheetah.jpg\")\n", " if text == \"Cheetah\"\n", " else Image.open(root / \"frog.jpg\")\n", " )\n", " img = img.resize((224, 224))\n", "\n", " return ([img, img, img, img], \"image\")\n", "\n", "block = gr.Blocks()\n", "\n", "examples = [\n", " [\"A serious capybara at work, wearing a suit\", 7],\n", " [\"A Squirtle fine dining with a view to the London Eye\", 7],\n", " [\"A tamale food cart in front of a Japanese Castle\", 7],\n", " [\"a graffiti of a robot serving meals to people\", 7],\n", " [\"a beautiful cabin in Attersee, Austria, 3d animation style\", 7],\n", "]\n", "\n", "with block as demo:\n", " with gr.Row(elem_id=\"prompt-container\", equal_height=True):\n", " text = gr.Textbox(\n", " label=\"Enter your prompt\",\n", " show_label=False,\n", " max_lines=1,\n", " placeholder=\"Enter your prompt\",\n", " elem_id=\"prompt-text-input\",\n", " )\n", "\n", " gallery = gr.Gallery(\n", " label=\"Generated images\", show_label=False, elem_id=\"gallery\", rows=2, columns=2\n", " )\n", " out_txt = gr.Textbox(\n", " label=\"Prompt\",\n", " placeholder=\"Enter a prompt to generate an image\",\n", " lines=3,\n", " elem_id=\"prompt-text-input\",\n", " )\n", "\n", " guidance_scale = gr.Slider(\n", " label=\"Guidance Scale\", minimum=0, maximum=50, value=7.5, step=0.1\n", " )\n", "\n", " ex = gr.Examples(\n", " examples=examples,\n", " fn=infer,\n", " inputs=[text, guidance_scale],\n", " outputs=[gallery, out_txt],\n", " cache_examples=True,\n", " )\n", "\n", " text.submit(\n", " infer,\n", " inputs=[text, guidance_scale],\n", " outputs=[gallery, out_txt],\n", " concurrency_id=\"infer\",\n", " concurrency_limit=8,\n", " )\n", "\n", "with gr.Blocks() as demo:\n", " block.render()\n", "\n", "if __name__ == \"__main__\":\n", " demo.queue(max_size=10, api_open=False).launch(show_api=False)\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
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