Spaces:
Runtime error
Runtime error
added check of temp files
Browse files- app.py +7 -3
- check_image_extraction.py +42 -0
- utils.py +6 -8
app.py
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@@ -1,14 +1,18 @@
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import gradio as gr
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from textblob import TextBlob
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import
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import tempfile
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def answer_video_question(query : str, url : str, file : bytes) -> dict:
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# Either `file` or `url` must be provided
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if file is not None:
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with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as temp_vid:
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temp_vid.write(file
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temp_video_path = temp_vid.name
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# Output frame folder
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@@ -31,7 +35,7 @@ demo = gr.Interface(
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inputs=[
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gr.Textbox(placeholder="Enter Query about the movie", label="Query"),
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gr.Textbox(placeholder="Paste the URL of the movie", label="Movie URL (optional)"),
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gr.File(label="Upload Movie File (optional)")
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],
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outputs=gr.JSON(),
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title="Text Sentiment Analysis",
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import gradio as gr
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from textblob import TextBlob
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from utils import *
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import tempfile
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def answer_video_question(query : str, url : str, file : bytes) -> dict:
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# Either `file` or `url` must be provided
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output_path='/tmp/video'
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if not os.path.exists(output_path):
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os.mkdir(output_path)
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if file is not None:
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with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as temp_vid:
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temp_vid.write(file)
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temp_video_path = temp_vid.name
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# Output frame folder
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inputs=[
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gr.Textbox(placeholder="Enter Query about the movie", label="Query"),
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gr.Textbox(placeholder="Paste the URL of the movie", label="Movie URL (optional)"),
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gr.File(label="Upload Movie File (optional)",type='binary')
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],
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outputs=gr.JSON(),
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title="Text Sentiment Analysis",
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check_image_extraction.py
ADDED
@@ -0,0 +1,42 @@
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import gradio as gr
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import os
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# Get all images in the folder, sorted by filename
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image_dir = "/tmp/video/frames"
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image_paths = sorted([
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os.path.join(image_dir, f)
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for f in os.listdir(image_dir)
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if f.endswith(".jpg")
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])
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def get_image(index):
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# Make sure the index is within bounds
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if 0 <= index < len(image_paths):
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return image_paths[index], index
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return None, index # No change if out of bounds
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def next_image(current_index):
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next_index = current_index + 1
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return get_image(next_index)
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def previous_image(current_index):
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prev_index = current_index - 1
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return get_image(prev_index)
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with gr.Blocks() as demo:
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gr.Markdown("### Browse Keyframes")
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image = gr.Image()
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index_state = gr.State(0) # Track current index
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with gr.Row():
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prev_btn = gr.Button("Previous")
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next_btn = gr.Button("Next")
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next_btn.click(fn=next_image, inputs=index_state, outputs=[image, index_state])
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prev_btn.click(fn=previous_image, inputs=index_state, outputs=[image, index_state])
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# Initialize with first image
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demo.load(fn=get_image, inputs=index_state, outputs=[image, index_state])
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demo.launch()
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utils.py
CHANGED
@@ -14,12 +14,12 @@ def download_video(url):
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"""
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# instanciate output path
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output_path='
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if not os.path.exists(output_path):
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os.mkdir(output_path)
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# get cookies
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export_cookies_path = "
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os.makedirs(os.path.dirname(export_cookies_path), exist_ok=True)
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try:
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ydl_opts_export_cookies = {
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@@ -72,7 +72,7 @@ def download_video(url):
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def is_significantly_different(img1, img2, threshold=0.
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"""Check if two images are significantly different using SSIM.
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Args:
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img1 (numpy.ndarray): First image.
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@@ -104,7 +104,7 @@ def extract_keyframes(video_path, diff_threshold=0.4):
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print("Failed to read video.")
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return
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output_path='
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if not os.path.exists(output_path):
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os.mkdir(output_path)
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@@ -115,14 +115,12 @@ def extract_keyframes(video_path, diff_threshold=0.4):
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frame_id += 1
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if is_significantly_different(prev_frame, frame, threshold=diff_threshold):
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filename = os.path.join("
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cv2.imwrite(filename, frame)
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prev_frame = frame
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saved_id += 1
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cap.release()
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print(f"Extracted {saved_id} key frames.")
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return "success"
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# Example usage
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extract_keyframes(video_path)
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"""
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# instanciate output path
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output_path='/tmp'
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if not os.path.exists(output_path):
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os.mkdir(output_path)
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# get cookies
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export_cookies_path = "/tmp/exported_cookies.txt"
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os.makedirs(os.path.dirname(export_cookies_path), exist_ok=True)
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try:
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ydl_opts_export_cookies = {
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def is_significantly_different(img1, img2, threshold=0.1):
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"""Check if two images are significantly different using SSIM.
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Args:
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img1 (numpy.ndarray): First image.
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print("Failed to read video.")
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return
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output_path='/tmp/video/frames'
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if not os.path.exists(output_path):
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os.mkdir(output_path)
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frame_id += 1
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if is_significantly_different(prev_frame, frame, threshold=diff_threshold):
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filename = os.path.join("/tmp/video/frames/",f"keyframe_{saved_id:04d}.jpg")
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cv2.imwrite(filename, frame)
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prev_frame = frame
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saved_id += 1
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print(f"frame{saved_id} saved")
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cap.release()
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print(f"Extracted {saved_id} key frames.")
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return "success"
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