IgorKir16/icicle-detector

🧊 Icicle Detector – YOLO26x model

This model is trained for automatic detection of icicles on images of building roofs and facades.
It detects one class – icicle – and outputs bounding boxes around each detected icicle.

Architecture: YOLO26x (custom modification based on YOLO).
Weights file: model.pt

Inference example

from ultralytics import YOLO
import cv2

# Load the model from Hugging Face
model = YOLO("IgorKir16/icicle-detector/model.pt")

# Run detection on an image
results = model("path/to/your_image.jpg", conf=0.25)

# Visualize results
for r in results:
    im_array = r.plot()
    cv2.imshow("Result", im_array)
    cv2.waitKey(0)

# Print bounding boxes and confidence
for r in results:
    for box in r.boxes:
        x1, y1, x2, y2 = box.xyxy[0].tolist()
        conf = box.conf[0].item()
        cls = int(box.cls[0].item())
        print(f"icicle: ({int(x1)}, {int(y1)}) – ({int(x2)}, {int(y2)}), confidence: {conf:.2f}")