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379b6f662e
* changes * changes * fix demo notebook * changes * changes * chagnes * changes * changes --------- Co-authored-by: Abubakar Abid <abubakar@huggingface.co>
46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
import gradio as gr
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import numpy as np
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with gr.Blocks() as demo:
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tolerance = gr.Slider(label="Tolerance", info="How different colors can be in a segment.", minimum=0, maximum=256*3, value=50)
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with gr.Row():
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input_img = gr.Image(label="Input")
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output_img = gr.Image(label="Selected Segment")
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def get_select_coords(img, tolerance, evt: gr.SelectData):
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visited_pixels = set()
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pixels_in_queue = set()
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pixels_in_segment = set()
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start_pixel = img[evt.index[1], evt.index[0]]
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pixels_in_queue.add((evt.index[1], evt.index[0]))
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while len(pixels_in_queue) > 0:
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pixel = pixels_in_queue.pop()
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visited_pixels.add(pixel)
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neighbors = []
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if pixel[0] > 0:
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neighbors.append((pixel[0] - 1, pixel[1]))
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if pixel[0] < img.shape[0] - 1:
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neighbors.append((pixel[0] + 1, pixel[1]))
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if pixel[1] > 0:
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neighbors.append((pixel[0], pixel[1] - 1))
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if pixel[1] < img.shape[1] - 1:
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neighbors.append((pixel[0], pixel[1] + 1))
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for neighbor in neighbors:
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if neighbor in visited_pixels:
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continue
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neighbor_pixel = img[neighbor[0], neighbor[1]]
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if np.abs(neighbor_pixel - start_pixel).sum() < tolerance:
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pixels_in_queue.add(neighbor)
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pixels_in_segment.add(neighbor)
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out = img.copy() * 0.2
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out = out.astype(np.uint8)
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for pixel in pixels_in_segment:
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out[pixel[0], pixel[1]] = img[pixel[0], pixel[1]]
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return out
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input_img.select(get_select_coords, [input_img, tolerance], output_img)
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if __name__ == "__main__":
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demo.launch()
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