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Jesteban247/
yolo11-blood_cell-onnx

Name: yolo11-blood_cell-onnx
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🩸 YOLO11 — Blood Cell Detector (Freeze-10, FP16 ONNX)

This model is a fine-tuned YOLO11 trained for blood cell detection on the
Blood Cell Dataset (Roboflow).
The first 10 layers were frozen to retain pretrained spatial features, and the model was exported to ONNX (FP16) for efficient inference.

⚙️ Configuration

Attribute	Value
Base Model	`yolo11n.pt`
Dataset	Blood Cell (Roboflow)
Epochs	30
Batch Size	32
Image Size	640×640
Optimizer	Auto
Freeze Layers	10
Precision	FP16 (half=True)
Export Format	ONNX
Device	GPU (0,1)

🩺 Example Detection

📈 Results

Metric	Value
mAP50	0.974
mAP50-95	0.905
Precision (B)	0.951
Recall (B)	0.920
Inference Time (ms)	33.73
FPS	29.65
Model Size (MB)	5.2

FP16 inference maintained identical accuracy to FP32 while reducing latency.
Layer freezing improved training stability and avoided overfitting on the limited dataset.

Jesteban247/yolo11-blood_cell-onnx

🩸 YOLO11 — Blood Cell Detector (Freeze-10, FP16 ONNX)

⚙️ Configuration

🩺 Example Detection

📈 Results

Jesteban247/
yolo11-blood_cell-onnx