Initial Gradio space

README.md

@@ -1,14 +1,45 @@
 ---
-title: Casting Defect Vit
-emoji: 🚀
-colorFrom: pink
-colorTo: green
+title: Casting Defect Detection
+emoji: 🔍
+colorFrom: green
+colorTo: gray
 sdk: gradio
-sdk_version: 6.19.0
-python_version: '3.13'
+sdk_version: 5.33.0
 app_file: app.py
 pinned: false
-license: cc
+license: mit
+models:
+  - gfichetdc/casting-defect-vit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Casting Defect Detection (ViT)
+
+Fine-tuned **ViT-B/16** on 6,633 casting surface images to classify parts as **defective** or **ok**.
+
+| Metric | Value |
+|--------|-------|
+| Macro F1 | 0.995 |
+| Accuracy | 99.6% |
+| Base model | google/vit-base-patch16-224 |
+| Training images | 6,633 |
+| Test images | 715 |
+| Epochs | 3 |
+
+## Usage
+
+```python
+from transformers import pipeline
+
+classifier = pipeline("image-classification", model="gfichetdc/casting-defect-vit")
+result = classifier("path/to/casting_image.jpeg")
+```
+
+## Dataset
+
+[Kaggle — Casting Product Image Data for Quality Inspection](https://www.kaggle.com/datasets/ravirajsinh45/real-life-industrial-dataset-of-casting-product): 7,348 grayscale images of submersible pump impellers.
+
+## Training
+
+- Fine-tuned `google/vit-base-patch16-224` with HuggingFace Trainer
+- lr=2e-5, batch size 16, 3 epochs on RTX 3060 (~10 min)
+- Experiment tracking with MLflow

app.py

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+import gradio as gr
+from transformers import pipeline
+
+classifier = pipeline("image-classification", model="gfichetdc/casting-defect-vit")
+
+def predict(image):
+    results = classifier(image)
+    return {r["label"]: r["score"] for r in results}
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(num_top_classes=2),
+    title="Casting Defect Detection (ViT)",
+    description="Fine-tuned ViT-B/16 classifying casting surface images as defective or ok. 99.5% macro F1.",
+    examples=[],
+)
+
+demo.launch()

requirements.txt

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+torch
+transformers
+Pillow