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# Models Directory
This directory will contain the ONNX models after conversion.
## Structure
After running the conversion scripts, this directory will contain:
```
models/
├── classifier_model_compressed/
│ ├── model.onnx # ONNX model for embryo detection
│ ├── config.json # Model configuration
│ └── preprocessor_config.json # Image preprocessing config
│
├── poor_good_compressed/
│ ├── model.onnx # ONNX model for quality assessment
│ ├── config.json # Model configuration
│ └── preprocessor_config.json # Image preprocessing config
│
├── grader_model_compressed/
│ ├── model.onnx # ONNX model for Gardner grading
│ ├── config.json # Model configuration
│ └── preprocessor_config.json # Image preprocessing config
│
└── yolo-cropper/
└── best.onnx # ONNX model for embryo detection
```
## How to Generate Models
Run the conversion scripts from the parent directory:
```bash
# Convert SigLIP models
python convert_to_onnx.py
# Convert YOLO model
python convert_yolo_to_onnx.py
```
## Model Sizes (Approximate)
- Classifier: ~95 MB
- Poor/Good: ~95 MB
- Grader: ~95 MB
- YOLO: ~6 MB
Total: ~290 MB
## Note
These models are not included in the repository due to their size.
You must convert them from the original PyTorch models.
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