Update chatgpt-ad-maker.py
Browse files- chatgpt-ad-maker.py +61 -11
chatgpt-ad-maker.py
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@@ -35,18 +35,68 @@ def create_dot_effect(image, dot_size=10, spacing=2):
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return canvas
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# Create Gradio interface
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gr.
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if __name__ == "__main__":
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iface.launch()
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return canvas
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def process_video(video_path, dot_size=10, spacing=2):
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# Read the video
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cap = cv2.VideoCapture(video_path)
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if not cap.isOpened():
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return None
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# Get video properties
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fps = int(cap.get(cv2.CAP_PROP_FPS))
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frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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# Create temporary output file with mp4v codec
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output_path = "temp_output.mp4"
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fourcc = cv2.VideoWriter_fourcc(*'avc1') # Changed from 'mp4v' to 'avc1' (h264 codec)
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out = cv2.VideoWriter(output_path, fourcc, fps, (frame_width, frame_height), False)
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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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# Convert BGR to RGB for processing
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frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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# Apply dot effect
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dotted_frame = create_dot_effect(frame_rgb, dot_size, spacing)
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out.write(dotted_frame)
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cap.release()
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out.release()
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return output_path
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# Create Gradio interface
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with gr.Blocks(title="ChatGPT Ad Maker") as iface:
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gr.Markdown("# ChatGPT Ad Maker")
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gr.Markdown("Convert your image or video into a dotted pattern. Adjust dot size and spacing using the sliders.")
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with gr.Tab("Image"):
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image_input = gr.Image(label="Input Image")
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with gr.Row():
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img_dot_size = gr.Slider(minimum=2, maximum=20, value=10, step=1, label="Dot Size")
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img_spacing = gr.Slider(minimum=0, maximum=10, value=2, step=1, label="Dot Spacing")
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image_output = gr.Image(label="Dotted Output")
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image_button = gr.Button("Process Image")
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image_button.click(
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fn=create_dot_effect,
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inputs=[image_input, img_dot_size, img_spacing],
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outputs=image_output
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)
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with gr.Tab("Video"):
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video_input = gr.Video(label="Input Video")
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with gr.Row():
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vid_dot_size = gr.Slider(minimum=2, maximum=20, value=10, step=1, label="Dot Size")
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vid_spacing = gr.Slider(minimum=0, maximum=10, value=2, step=1, label="Dot Spacing")
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video_output = gr.Video(label="Dotted Output", format="mp4")
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video_button = gr.Button("Process Video")
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video_button.click(
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fn=process_video,
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inputs=[video_input, vid_dot_size, vid_spacing],
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outputs=video_output
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)
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if __name__ == "__main__":
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iface.launch()
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