updates to algorithm

visualizeCount.py

@@ -0,0 +1,77 @@
+import cv2
+import numpy as np
+from ultralytics import YOLO
+import cvzone
+
+device = 'cuda'
+
+# Load the YOLO11 model
+model = YOLO("yolo11m-pecan.pt")
+
+# Open the video file (use video file or webcam, here using webcam)
+cap = cv2.VideoCapture(0)
+cy1=550
+offset=60
+idDict={}
+pecanCount = 0
+
+# Define the desired resolution and FPS
+width, height = 1280, 720
+
+# Set the resolution and other properties for each camera
+cap.set(cv2.CAP_PROP_FRAME_WIDTH, width)
+cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
+
+while True:
+    ret,frame = cap.read()
+    if not ret:
+        break
+    
+    # Define the black box position (adjust as needed)
+    top_left = (0, 0) 
+    bottom_right = (1280, 220)  
+
+    # Draw a black rectangle (filled)
+    cv2.rectangle(frame, top_left, bottom_right, (0, 0, 0), thickness=-1)
+
+    # Run YOLO11 tracking on the frame, persisting tracks between frames
+    results = model.track(frame, persist=True,classes=0,device = device)
+
+    # Check if there are any boxes in the results
+    if results[0].boxes is not None and results[0].boxes.id is not None:
+        # Get the boxes (x, y, w, h), class IDs, track IDs, and confidences
+        boxes = results[0].boxes.xyxy.int().cpu().tolist()  # Bounding boxes
+        class_ids = results[0].boxes.cls.int().cpu().tolist()  # Class IDs
+        track_ids = results[0].boxes.id.int().cpu().tolist()  # Track IDs
+        confidences = results[0].boxes.conf.cpu().tolist()  # Confidence score
+       
+        for box, class_id, track_id, conf in zip(boxes, class_ids, track_ids, confidences):
+            x1, y1, x2, y2 = box
+            cy = int(y1+y2)//2
+            if track_id in idDict.keys():
+                cv2.rectangle(frame,(x1,y1),(x2,y2),(255,255,255),2)
+                cvzone.putTextRect(frame,f'{idDict[track_id]}',(x1,y2),1,1)
+            else:
+                cv2.rectangle(frame,(x1,y1),(x2,y2),(0,255,0),2)
+                # cvzone.putTextRect(frame,f'{track_id}',(x1,y2),1,1)
+            # cv2.circle(frame,(cx,cy),4,(255,0,0),-1)
+            # cvzone.putTextRect(frame,f'{c}',(x1,y1),1,1)
+            if cy<(cy1+offset) and cy>(cy1-offset) and track_id not in idDict.keys():
+                pecanCount += 1
+                idDict[track_id] = pecanCount
+            cv2.putText(frame, f'Totals Pecans: {pecanCount}', (50, 50),cv2.FONT_HERSHEY_SIMPLEX, 
+                    0.6, [255, 255, 255], 1)
+            
+    cv2.line(frame,(0,550),(1280,550),(255,0,255),2)
+    cv2.line(frame,(0,cy1+offset),(1280,cy1+offset),(0,0,255),2)
+    cv2.line(frame,(0,cy1-offset),(1280,cy1-offset),(0,0,255),2)
+
+    cv2.imshow('Frame', frame)
+    cv2.imshow("RGB", frame)
+    if cv2.waitKey(1) & 0xFF == ord("q"):
+       break
+
+# Release the video capture object and close the display window
+cap.release()
+cv2.destroyAllWindows()
+print(pecanCount)