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