Create pothole_detection._and_instance_segmentation_yolov8

pothole_detection._and_instance_segmentation_yolov8

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+from ultralytics import YOLO
+import cv2
+import numpy as np
+
+# Load the model
+model = YOLO("best.pt")
+class_names = model.names
+cap = cv2.VideoCapture('p.mp4')
+count = 0
+
+while True:
+    ret, img = cap.read()
+    if not ret:
+        break  # Break if no frames are left in the video
+    count += 1
+    if count % 3 != 0:  # Skip frames to process every 3rd frame
+        continue
+
+    img = cv2.resize(img, (1020, 500))
+    h, w, _ = img.shape
+    results = model.predict(img)
+
+    for r in results:
+        boxes = r.boxes  # Bounding boxes
+        masks = r.masks  # Segmentation masks if available
+
+    if masks is not None:
+        masks = masks.data.cpu()
+        for seg, box in zip(masks.numpy(), boxes):
+            seg = cv2.resize(seg, (w, h))
+            contours, _ = cv2.findContours((seg).astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+            for contour in contours:
+                d = int(box.cls)
+                c = class_names[d]
+                x, y, x1, y1 = cv2.boundingRect(contour)
+                cv2.polylines(img, [contour], True, color=(0, 0, 255), thickness=2)
+                cv2.rectangle(img, (x, y), (x1 + x, y1 + y), (255, 0, 0), 2)
+                cv2.putText(img, c, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)
+
+    cv2.imshow('Video', img)
+    if cv2.waitKey(1) & 0xFF == ord('q'):  # Play video with a delay of 1ms
+        break
+
+cap.release()
+cv2.destroyAllWindows()
+