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README.md

@@ -6,24 +6,31 @@ tags:
 - pytorch
 datasets:
 - wendys-llc/chkbx
+widget:
+- src: https://i.imgur.com/ExampleChecked.jpg
+  candidate_labels: unchecked, checked
+  example_title: Checked Box
+- src: https://i.imgur.com/ExampleUnchecked.jpg  
+  candidate_labels: unchecked, checked
+  example_title: Unchecked Box
 ---
 
 # Checkbox Classifier
 
-Binary classifier for checkbox states (checked/unchecked).
+Binary classifier for checkbox states (checked/unchecked). Trained on the [wendys-llc/chkbx](https://huggingface.co/datasets/wendys-llc/chkbx) dataset.
 
-## Usage with Transformers
+## Usage
 
 ```python
 from transformers import pipeline
+from PIL import Image
 
 # Load pipeline
 classifier = pipeline("image-classification", 
                      model="wendys-llc/checkbox-classifier", 
                      trust_remote_code=True)
 
-# Predict
-from PIL import Image
+# Classify an image
 image = Image.open("checkbox.jpg")
 result = classifier(image)
 print(result)
@@ -31,30 +38,29 @@ print(result)
 #   {'label': 'checked', 'score': 0.99},
 #   {'label': 'unchecked', 'score': 0.01}
 # ]
+
+# Get just the top prediction
+top_result = classifier(image, top_k=1)
+print(f"State: {top_result[0]['label']}")
 ```
 
-## Direct Usage
+## Model Details
 
-```python
-from transformers import AutoModelForImageClassification, AutoImageProcessor
-import torch
-from PIL import Image
+- **Architecture**: EfficientNetV2-S
+- **Input Size**: 128x128 RGB images  
+- **Training**: Mixed precision on A100 GPU
+- **Validation Accuracy**: 97.1%
+- **License**: Apache 2.0
 
-model = AutoModelForImageClassification.from_pretrained(
-    "wendys-llc/checkbox-classifier", 
-    trust_remote_code=True
-)
-processor = AutoImageProcessor.from_pretrained("wendys-llc/checkbox-classifier")
+## Intended Use
 
-image = Image.open("checkbox.jpg")
-inputs = processor(images=image, return_tensors="pt")
-
-with torch.no_grad():
-    outputs = model(**inputs)
-    logits = outputs.logits
-    predicted_class = logits.argmax(-1).item()
-    
-print(model.config.id2label[predicted_class])
-```
+This model is designed to classify UI checkboxes in screenshots or interface images. It works best on:
+- Clear, high-contrast checkbox images
+- Standard UI checkboxes (not hand-drawn)
+- Images where the checkbox is the main focus
+
+## Limitations
 
-## Accuracy: 97.1%
+- May not work well on hand-drawn checkmarks
+- Trained on UI checkboxes, not paper forms
+- Best performance when checkbox is clearly visible and not too small