# 📦 Hugging Face Deployment - File Checklist

## ✅ Files Created for Deployment

### Core Application Files

- ✅ **app.py** - Gradio interface with OCR processing
- ✅ **requirements.txt** - Python dependencies (Gradio + eDOCr2)
- ✅ **packages.txt** - System dependencies (Tesseract, Poppler)
- ✅ **README.md** - Space description with YAML frontmatter
- ✅ **.gitattributes** - Git LFS configuration for model files

### Documentation

- ✅ **DEPLOYMENT.md** - Complete deployment guide
- ✅ **run_local.bat** - Windows quick start script
- ✅ **run_local.sh** - Linux/Mac quick start script

### Required Folders

- ✅ **edocr2/** - Main package (already exists)
  - ✅ **edocr2/tools/** - OCR pipelines
  - ✅ **edocr2/keras_ocr/** - OCR models
  - ⚠️ **edocr2/models/** - Model files (MUST DOWNLOAD)

- ✅ **tests/test_samples/** - Example drawings (optional)

## 🔴 IMPORTANT: Download Model Files

Before deploying, download these 4 files and place in `edocr2/models/`:

1. **recognizer_gdts.keras** (67.2 MB)
2. **recognizer_gdts.txt** (85 bytes)
3. **recognizer_dimensions_2.keras** (67.2 MB)
4. **recognizer_dimensions_2.txt** (42 bytes)

**Download from:** https://github.com/javvi51/edocr2/releases/tag/v1.0.0

## 📋 Pre-Deployment Checklist

### Local Testing

- [ ] Models downloaded and placed in `edocr2/models/`
- [ ] Run `python app.py` locally
- [ ] Test with sample images
- [ ] Verify all outputs (image, JSON, ZIP)

### Hugging Face Setup

- [ ] Hugging Face account created
- [ ] Git LFS installed
- [ ] New Space created on Hugging Face

### File Verification

- [ ] All files present in folder
- [ ] Model files in correct location
- [ ] `.gitattributes` configured for LFS
- [ ] `README.md` has YAML frontmatter

## 🚀 Deployment Steps

### 1. Download Models

**Windows PowerShell:**
```powershell
cd edocr2-main
New-Item -ItemType Directory -Force -Path edocr2\models
cd edocr2\models

Invoke-WebRequest -Uri "https://github.com/javvi51/edocr2/releases/download/v1.0.0/recognizer_gdts.keras" -OutFile "recognizer_gdts.keras"
Invoke-WebRequest -Uri "https://github.com/javvi51/edocr2/releases/download/v1.0.0/recognizer_gdts.txt" -OutFile "recognizer_gdts.txt"
Invoke-WebRequest -Uri "https://github.com/javvi51/edocr2/releases/download/v1.0.0/recognizer_dimensions_2.keras" -OutFile "recognizer_dimensions_2.keras"
Invoke-WebRequest -Uri "https://github.com/javvi51/edocr2/releases/download/v1.0.0/recognizer_dimensions_2.txt" -OutFile "recognizer_dimensions_2.txt"

cd ..\..
```

**Linux/Mac:**
```bash
cd edocr2-main
mkdir -p edocr2/models
cd edocr2/models

wget https://github.com/javvi51/edocr2/releases/download/v1.0.0/recognizer_gdts.keras
wget https://github.com/javvi51/edocr2/releases/download/v1.0.0/recognizer_gdts.txt
wget https://github.com/javvi51/edocr2/releases/download/v1.0.0/recognizer_dimensions_2.keras
wget https://github.com/javvi51/edocr2/releases/download/v1.0.0/recognizer_dimensions_2.txt

cd ../..
```

### 2. Test Locally (Optional but Recommended)

**Windows:**
```bash
run_local.bat
```

**Linux/Mac:**
```bash
chmod +x run_local.sh
./run_local.sh
```

Open: http://localhost:7860

### 3. Create Hugging Face Space

1. Go to https://huggingface.co/spaces
2. Click "Create new Space"
3. Settings:
   - Name: `edocr2` (or your choice)
   - License: MIT
   - SDK: Gradio
   - Hardware: CPU Basic (free)

### 4. Clone Space Repository

```bash
git clone https://huggingface.co/spaces/YOUR_USERNAME/edocr2
cd edocr2
```

### 5. Copy Files

**Windows:**
```bash
xcopy /E /I C:\path\to\edocr2-main\* .
```

**Linux/Mac:**
```bash
cp -r /path/to/edocr2-main/* .
```

### 6. Setup Git LFS

```bash
git lfs install
git lfs track "*.keras"
git add .gitattributes
```

### 7. Commit and Push

```bash
git add .
git commit -m "Initial deployment of eDOCr2"
git push origin main
```

**Note:** Upload may take 5-10 minutes for large model files.

### 8. Wait for Build

- Go to your Space URL
- Wait 5-10 minutes for build
- Check "Logs" tab for errors

## ✅ Verification

Once deployed:

- [ ] Space shows Gradio interface
- [ ] Models load successfully (check logs)
- [ ] Can upload images
- [ ] Processing works
- [ ] Results display correctly
- [ ] Download ZIP works

## 🎯 Your Space URL

After deployment, your Space will be at:

```
https://huggingface.co/spaces/YOUR_USERNAME/edocr2
```

## 📊 Expected Performance

### CPU Basic (Free)
- Processing time: 20-30 seconds per image
- Memory: 2 GB RAM
- Cost: FREE

### T4 GPU (Paid)
- Processing time: 5-10 seconds per image
- Memory: 16 GB RAM
- Cost: $0.60/hour

## 🐛 Common Issues

### "Models not found"
- Ensure models are in `edocr2/models/`
- Check Git LFS tracked the files
- Verify file names are correct

### "Out of memory"
- Upgrade to GPU hardware
- Or reduce `max_img_size` in app.py

### "Build failed"
- Check logs for specific error
- Verify all dependencies in requirements.txt
- Ensure packages.txt has system deps

## 📚 Resources

- **Deployment Guide**: See `DEPLOYMENT.md`
- **Hugging Face Docs**: https://huggingface.co/docs/hub/spaces
- **Gradio Docs**: https://gradio.app/docs
- **Original Repo**: https://github.com/javvi51/edocr2

## 🎉 Success!

Once deployed, share your Space:

```
🔗 https://huggingface.co/spaces/YOUR_USERNAME/edocr2
```

---

**Questions?** Check `DEPLOYMENT.md` for detailed troubleshooting.