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Parent(s):
0a08c3a
Update app.py
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app.py
CHANGED
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import gradio as gr
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def
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import gradio as gr
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import cv2
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import numpy as np
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import watershed # Your Python bindings module
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def segment_image(input_image):
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# Convert the image received from Gradio into a format suitable for our C++ function
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is_success, im_buf_arr = cv2.imencode(".jpg", input_image)
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byte_im = im_buf_arr.tobytes()
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# You can save this to a file or directly pass it if your C++ function can handle byte streams
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with open("temp_input.jpg", "wb") as f:
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f.write(byte_im)
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# Call the C++ watershed_segmentation function
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watershed.watershed_segmentation("temp_input.jpg", "output.jpg")
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# Read the output image to display in Gradio
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output_img = cv2.imread("output.jpg")
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# Convert from BGR (OpenCV format) to RGB (for displaying in Gradio)
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output_img = cv2.cvtColor(output_img, cv2.COLOR_BGR2RGB)
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return output_img
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# Define Gradio interface
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interface = gr.Interface(
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fn=segment_image,
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inputs=gr.inputs.Image(type="numpy", label="Input Image"),
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outputs=gr.outputs.Image(type="numpy", label="Segmented Image"),
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live=True,
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title="Watershed Image Segmentation",
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description="Upload an image for watershed segmentation."
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)
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interface.launch()
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