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Upload 4 files
Browse files- app.py +46 -0
- best.pt +3 -0
- pothole_example.jpg +0 -0
- pothole_screenshot.png +0 -0
app.py
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import gradio as gr
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import cv2
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import requests
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import os
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from ultralytics import YOLO
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model = YOLO('best.pt')
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image_paths = ['pothole_example.jpg', 'pothole_screenshot.png']
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def show_preds_image(image):
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# Save the uploaded image temporarily
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image_path = "uploaded_image.jpg"
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cv2.imwrite(image_path, image[:, :, ::-1]) # Convert BGR to RGB and save the image
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image = cv2.imread(image_path)
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outputs = model.predict(source=image_path)
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results = outputs[0].cpu().numpy()
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for i, det in enumerate(results.boxes.xyxy):
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cv2.rectangle(
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image,
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(int(det[0]), int(det[1])),
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(int(det[2]), int(det[3])),
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color=(0, 0, 255),
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thickness=2,
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lineType=cv2.LINE_AA
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)
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os.remove(image_path) # Remove the temporary image file
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return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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inputs_image = [
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gr.inputs.Image(label="Upload Image"),
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]
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outputs_image = [
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gr.outputs.Image(type="numpy"),
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]
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interface_image = gr.Interface(
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fn=show_preds_image,
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inputs=inputs_image,
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outputs=outputs_image,
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title="Pothole detector",
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examples=[],
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cache_examples=False,
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)
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interface_image.launch()
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best.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:ce9a23590d666fcca004d3a2330f3e30b229bbe9df0dbf4b0fd390c20fbe67fe
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size 6233272
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pothole_example.jpg
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pothole_screenshot.png
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