Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,54 @@
+---
+license: mit
+tags:
+- image-classification
+- computer-vision
+- defect-detection
+- automotive
+- pytorch
+- timm
+- efficientnet
+language:
+- ru
+pipeline_tag: image-classification
+---
+
+# Paint Defect Detector
+
+A binary image classifier that detects **paint defects** on car body panels using transfer learning with EfficientNetV2-S backbone (via 	imm).
+
+## Model Architecture
+
+- **Backbone**: EfficientNetV2-S (pretrained, from 	imm)
+- **Head**: Dropout → Linear(feat_dim, 256) → GELU → Dropout → Linear(256, 2)
+- **Task**: Binary classification — clean vs defect
+
+## Training
+
+- **Optimizer**: AdamW with cosine annealing LR scheduler
+- **Loss**: CrossEntropyLoss with label smoothing
+- **Augmentations**: Albumentations pipeline
+- **Metrics**: AUC-ROC, F1, Accuracy
+
+## Inference
+
+The project includes a FastAPI REST API (src/api.py) for serving predictions, and a Grad-CAM visualisation layer for model explainability.
+
+## Project Structure
+
+`
+src/
+  config.py        # Hyperparameters and paths
+  dataset.py       # Dataset and data loaders
+  model.py         # DefectClassifier model
+  train.py         # Training loop
+  infer.py         # Inference utilities
+  api.py           # FastAPI inference server
+  prepare_data.py  # Data preparation script
+requirements.txt
+`
+
+## Requirements
+
+See 
+equirements.txt. Key dependencies: 	orch, 	imm, lbumentations, astapi, grad-cam.