Upload upload_instructions.md with huggingface_hub

upload_instructions.md

@@ -0,0 +1,51 @@
+# Upload Instructions for Hugging Face Space
+
+## Files to Upload
+
+Upload these files to your Hugging Face Space (in this order):
+
+### 1. Core Application Files
+- `app.py` - Main Gradio application
+- `README.md` - Space description
+- `requirements.txt` - Python dependencies
+- `package.json` - Node.js configuration
+
+### 2. Model Architecture Files
+- `convnext_original.py` - Original ConvNeXt model
+- `convnext_finetune.py` - Fine-tuned ConvNeXt model
+
+### 3. Sample Images
+- Upload the entire `sample_image/` folder with all images
+
+### 4. Model Weights (Download from Box first)
+**IMPORTANT**: Download these files from Box first: https://utexas.box.com/s/8aw6axc2lofouja65uc726lca8b1cduf
+
+Then create these directories and upload:
+- `feature_models/convnext_tiny_22k_224.pth` (170MB)
+- `feature_models/triqa_quality_aware.pth` (107MB)
+- `Regression_Models/KonIQ_scaler.save`
+- `Regression_Models/KonIQ_TRIQA.save` (111MB)
+
+## Upload Steps
+
+1. **Create the Space** on Hugging Face
+2. **Upload files** using the web interface or Git
+3. **Wait for build** (2-5 minutes)
+4. **Test the demo** with sample images
+
+## Expected Result
+
+The demo will show:
+- Image upload interface
+- Quality assessment button
+- Sample images for testing
+- Quality score output (1-5 scale)
+- Paper links and citation
+
+## Troubleshooting
+
+If the demo doesn't work:
+1. Check that all model files are uploaded
+2. Verify file paths are correct
+3. Check the Space logs for errors
+4. Ensure all dependencies are in requirements.txt