fruit-veg-yolo11l-detector

Fruit & Vegetable Object Detector (YOLO11l)

Fine-tuned YOLO11-large for detecting and counting fruits and vegetables in images.

Model Details

• Base model: yolo11l.pt (Ultralytics)
• Task: Object detection (bounding box + class)
• Classes (35): Apple, Banana, Beetroot, Bitter_Gourd, Bottle_Gourd, Cabbage, Capsicum, Carrot, Cauliflower, Cherry, Chilli, Coconut, Cucumber, EggPlant, Ginger, Grape, Green_Orange, Kiwi, Maize, Mango, Melon, Okra, Onion, Orange, Peach, Pear, Peas, Pineapple, Pomegranate, Potato, Radish, Strawberry, Tomato, Turnip, Watermelon
• Input size: 640x640
• Framework: Ultralytics YOLO11

Training

• Fine-tuned on Roboflow "Fruits and Vegi" dataset
• mAP50: 0.913
• mAP50-95: 0.689

Usage

from ultralytics import YOLO

model = YOLO("best.pt")
results = model.predict("your_image.jpg", conf=0.25)

for box in results[0].boxes:
    cls_name = model.names[int(box.cls[0])]
    conf = float(box.conf[0])
    print(f"{cls_name}: {conf:.2f}")