Commit
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7cd255e
1
Parent(s):
1ff63b5
fixing
Browse files- Dockerfile +6 -4
- services/summarizer.py +28 -14
Dockerfile
CHANGED
@@ -1,6 +1,3 @@
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# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
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# You will also find guides on how best to write your Dockerfile
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FROM python:3.12-slim
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ENV TORCH_HOME=/tmp/torch_cache
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@@ -9,7 +6,12 @@ WORKDIR /code
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COPY ./requirements.txt /code/requirements.txt
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RUN pip install --no-cache-dir --upgrade pip \
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&& pip install --no-cache-dir -r /code/requirements.txt
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FROM python:3.12-slim
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ENV TORCH_HOME=/tmp/torch_cache
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COPY ./requirements.txt /code/requirements.txt
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# Install ffmpeg along with other dependencies
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RUN apt-get update && apt-get install -y \
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libgl1 \
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libglib2.0-0 \
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ffmpeg \
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&& apt-get clean && rm -rf /var/lib/apt/lists/*
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RUN pip install --no-cache-dir --upgrade pip \
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&& pip install --no-cache-dir -r /code/requirements.txt
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services/summarizer.py
CHANGED
@@ -2,6 +2,9 @@ import cv2
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import torch
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from config import SCORE_THRESHOLD
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from services.model_loader import load_model
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model = load_model("Model/epoch-199.pkl")
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@@ -20,13 +23,12 @@ def get_scores(features):
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return scores
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def get_selected_indices(scores, picks, threshold=SCORE_THRESHOLD):
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print("Threshold for selection:", threshold)
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print("Scores:", scores
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print("Picks:", picks
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import subprocess
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import os
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def save_summary_video(video_path, selected_indices, output_path, fps=15):
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import cv2
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@@ -34,24 +36,36 @@ def save_summary_video(video_path, selected_indices, output_path, fps=15):
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cap = cv2.VideoCapture(video_path)
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selected = set(selected_indices)
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frame_id = 0
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frames =
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while cap.isOpened():
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ret, frame = cap.read()
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if not ret:
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break
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if frame_id in selected:
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frames
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frame_id += 1
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cap.release()
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if
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print("No frames selected.")
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return
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h, w, _ =
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import torch
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from config import SCORE_THRESHOLD
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from services.model_loader import load_model
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import subprocess
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import os
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import numpy as np
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model = load_model("Model/epoch-199.pkl")
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return scores
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def get_selected_indices(scores, picks, threshold=SCORE_THRESHOLD):
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selected = [picks[i] for i, score in enumerate(scores) if score >= threshold]
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print("Threshold for selection:", threshold)
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print("Scores:", len(scores), scores)
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print("Picks:", len(picks), picks)
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print("Selected indices:", len(selected), selected)
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return selected
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def save_summary_video(video_path, selected_indices, output_path, fps=15):
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import cv2
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cap = cv2.VideoCapture(video_path)
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selected = set(selected_indices)
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frame_id = 0
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frames = []
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while cap.isOpened():
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ret, frame = cap.read()
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if not ret:
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break
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if frame_id in selected:
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frames.append(frame)
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frame_id += 1
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cap.release()
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if len(frames) == 0:
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print("No frames selected.")
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return
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h, w, _ = frames[0].shape
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print("Video dimensions:", w, h)
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out = cv2.VideoWriter(output_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (h, w))
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for frame in frames:
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out.write(frame)
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out.release()
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print("Fixing the video with ffmpeg")
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# fix_video_with_ffmpeg(output_path)
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def fix_video_with_ffmpeg(path):
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temp_path = path + ".fixed.mp4"
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subprocess.run([
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"ffmpeg", "-y", "-i", path,
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"-vcodec", "libx264", "-pix_fmt", "yuv420p", temp_path
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])
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os.replace(temp_path, path)
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