4

app.py

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+import gradio as gr
+import cv2
+
+from ultralytics import YOLO
+
+model = YOLO('best.pt')
+path  = [['pothole1.jpg'], ['pothole2.jpg'], ['pothole3.jpg'],['pothole4.jpg']]
+
+import cv2
+
+def resize_image(image_path):
+    # Read the image using OpenCV
+    img = cv2.imread(image_path)
+
+    # Resize the image to 512x512
+    resized_img = cv2.resize(img, (512, 512), interpolation = cv2.INTER_LINEAR)
+
+    return resized_img
+
+
+def prediction1(image_path):
+    #image = resize_image(image_path)
+    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=(0,255, 0),
+            thickness=1,
+            lineType=cv2.LINE_AA,
+        )
+    return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
+inputs_image = [
+    gr.components.Image(type="filepath", label="Input Image"),
+]
+outputs_image = [
+    gr.components.Image(type="numpy", label="Output Image"),
+]
+interface_image = gr.Interface(
+    fn=prediction1,
+    inputs=inputs_image,
+    outputs=outputs_image,
+    title="Pothole detection",
+    description="Detects potholes in images",
+    #cache_examples=True,
+    examples=path
+    
+)
+
+
+
+interface_image.launch()

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ce9a23590d666fcca004d3a2330f3e30b229bbe9df0dbf4b0fd390c20fbe67fe
+size 6233272

requirements.txt

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+# Ultralytics requirements
+# Usage: pip install -r requirements.txt
+
+# Base ----------------------------------------
+hydra-core>=1.2.0
+matplotlib>=3.2.2
+numpy>=1.18.5
+opencv-python>=4.1.1
+Pillow>=7.1.2
+PyYAML>=5.3.1
+requests>=2.23.0
+scipy>=1.4.1
+torch>=1.7.0
+torchvision>=0.8.1
+tqdm>=4.64.0
+ultralytics
+
+# Logging -------------------------------------
+tensorboard>=2.4.1
+# clearml
+# comet
+
+# Plotting ------------------------------------
+pandas>=1.1.4
+seaborn>=0.11.0
+
+# Export --------------------------------------
+# coremltools>=6.0  # CoreML export
+# onnx>=1.12.0  # ONNX export
+# onnx-simplifier>=0.4.1  # ONNX simplifier
+# nvidia-pyindex  # TensorRT export
+# nvidia-tensorrt  # TensorRT export
+# scikit-learn==0.19.2  # CoreML quantization
+# tensorflow>=2.4.1  # TF exports (-cpu, -aarch64, -macos)
+# tensorflowjs>=3.9.0  # TF.js export
+# openvino-dev  # OpenVINO export
+
+# Extras --------------------------------------
+ipython  # interactive notebook
+psutil  # system utilization
+thop>=0.1.1  # FLOPs computation
+# albumentations>=1.0.3
+# pycocotools>=2.0.6  # COCO mAP
+# roboflow
+
+# HUB -----------------------------------------
+GitPython>=3.1.24