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Update app.py
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app.py
CHANGED
@@ -64,7 +64,7 @@ def create_video_from_frames(frame_files, output_path, duration_seconds, width,
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video.release()
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def process_svg_to_video(input_svg_path, original_width, original_height, video_duration_seconds=10, chunk_size=
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"""Process SVG file and create a video with specified duration using exact row slicing"""
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# Read SVG file as a table to maintain exact row slicing logic
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df = pd.read_table(input_svg_path, header=None)
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@@ -75,10 +75,12 @@ def process_svg_to_video(input_svg_path, original_width, original_height, video_
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# Use the original image dimensions
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width, height = original_width, original_height
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#
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total_rows = len(df_middle)
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if chunk_size
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chunk_size = max(1, total_rows // 30)
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# Create a temporary directory for images
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temp_dir = tempfile.mkdtemp()
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@@ -113,6 +115,7 @@ def process_svg_to_video(input_svg_path, original_width, original_height, video_
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def convert_to_vector_and_video(
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image,
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video_duration=10,
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colormode="color",
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hierarchical="stacked",
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mode="spline",
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@@ -158,7 +161,8 @@ def convert_to_vector_and_video(
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output_svg_path,
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original_width,
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original_height,
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video_duration_seconds=video_duration
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)
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# Read the SVG output
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@@ -179,6 +183,7 @@ def clear_inputs():
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return (
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gr.Image(value=None),
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gr.Slider(value=10),
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gr.Radio(value="color"),
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gr.Radio(value="stacked"),
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gr.Radio(value="spline"),
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@@ -243,6 +248,8 @@ with gr.Blocks(css=css) as app:
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with gr.Column():
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image_input = gr.Image(type="pil", label="Upload Image")
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video_duration = gr.Slider(1, 60, value=10, step=1, label="Video Duration (seconds)")
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with gr.Accordion("Advanced Settings", open=False):
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with gr.Accordion("Clustering", open=False):
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@@ -300,6 +307,7 @@ with gr.Blocks(css=css) as app:
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outputs=[
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image_input,
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video_duration,
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colormode,
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hierarchical,
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mode,
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@@ -319,6 +327,7 @@ with gr.Blocks(css=css) as app:
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inputs=[
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image_input,
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video_duration,
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colormode,
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hierarchical,
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mode,
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video.release()
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def process_svg_to_video(input_svg_path, original_width, original_height, video_duration_seconds=10, chunk_size=30):
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"""Process SVG file and create a video with specified duration using exact row slicing"""
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# Read SVG file as a table to maintain exact row slicing logic
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df = pd.read_table(input_svg_path, header=None)
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# Use the original image dimensions
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width, height = original_width, original_height
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# If chunk_size is 0, use automatic calculation (total_rows // 30)
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total_rows = len(df_middle)
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if chunk_size == 0:
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chunk_size = max(1, total_rows // 30)
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else:
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chunk_size = max(1, min(chunk_size, total_rows)) # Ensure it's within valid range
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# Create a temporary directory for images
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temp_dir = tempfile.mkdtemp()
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def convert_to_vector_and_video(
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image,
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video_duration=10,
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chunk_size=30,
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colormode="color",
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hierarchical="stacked",
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mode="spline",
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output_svg_path,
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original_width,
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original_height,
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video_duration_seconds=video_duration,
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chunk_size=chunk_size
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)
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# Read the SVG output
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return (
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gr.Image(value=None),
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gr.Slider(value=10),
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gr.Slider(value=30),
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gr.Radio(value="color"),
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gr.Radio(value="stacked"),
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gr.Radio(value="spline"),
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with gr.Column():
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image_input = gr.Image(type="pil", label="Upload Image")
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video_duration = gr.Slider(1, 60, value=10, step=1, label="Video Duration (seconds)")
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chunk_size = gr.Slider(0, 1000, value=30, step=1, label="Chunk Size (0=auto)",
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info="Number of SVG path elements to add per frame (0 for automatic calculation)")
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with gr.Accordion("Advanced Settings", open=False):
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with gr.Accordion("Clustering", open=False):
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outputs=[
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image_input,
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video_duration,
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chunk_size,
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colormode,
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hierarchical,
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mode,
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inputs=[
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image_input,
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video_duration,
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chunk_size,
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colormode,
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hierarchical,
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mode,
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