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IgorKir16/icicle-detector
icicle-detector is a machine learning model from IgorKir16. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
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.
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Updated Jun 18, 2026
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.pt118 MB · 100%
From the Hugging Face model README
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
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}")