Add requirements for YOLOv5

app.py

@@ -1,18 +1,17 @@
-from ultralytics import YOLO
-import gradio as gr
+import torch
+from yolov5.utils.general import non_max_suppression, scale_coords
+from yolov5.utils.plots import plot_boxes
+from yolov5.models.common import DetectMultiBackend
 from PIL import Image
+import numpy as np
 
-model = YOLO("best.pt")  
-def detect_potholes(image):
-    results = model(image)
-    annotated_frame = results[0].plot()  
-    return Image.fromarray(annotated_frame)
+model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt') 
 
-iface = gr.Interface(
-    fn=detect_potholes,
-    inputs=gr.inputs.Image(type="pil"),
-    outputs="image",
-    title="Pothole Detector"
-)
+def detect(image):
+    results = model(image)
+    return results 
 
-iface.launch()
+# Example inference
+image = Image.open("test.jpg")
+results = detect(image)
+print(results)

requirements.txt

@@ -5,3 +5,9 @@ opencv-python
 numpy
 pillow
 gradio
+torch
+torchvision
+numpy
+opencv-python
+pillow
+git+https://github.com/ultralytics/yolov5.git

yolov5

@@ -0,0 +1 @@
+Subproject commit de62f93c210aaaffd710f9afe3b43ab624f7a21b