File size: 3,914 Bytes
fff3c77 7149c09 fff3c77 7149c09 fff3c77 7149c09 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 | ---
title: Milk Spoilage Classifier - Multi-Variant API
emoji: 🥛
colorFrom: indigo
colorTo: purple
sdk: docker
pinned: false
license: mit
---
# Milk Spoilage Classification API - Multi-Variant
AI-powered milk spoilage classification with **10 specialized model variants** optimized for different data availability scenarios.
## 🚀 Features
- **10 Model Variants** with test accuracies from 62.8% to 95.8%
- **Automatic Feature Validation** - API validates required features for each variant
- **RESTful API** with comprehensive OpenAPI documentation
- **Custom GPT Ready** - Designed for seamless ChatGPT integration
## 📊 Available Model Variants
| Rank | Variant | Test Accuracy | Features Required |
|------|---------|---------------|-------------------|
| 🥇 | baseline | **95.8%** | All 6 features |
| 🥈 | scenario_1_days14_21 | **94.2%** | Days 14 & 21 (SPC+TGN) |
| 🥉 | scenario_3_day21 | **93.7%** | Day 21 only (SPC+TGN) |
| 4 | scenario_4_day14 | 87.4% | Day 14 only (SPC+TGN) |
| 5 | scenario_2_days7_14 | 87.3% | Days 7 & 14 (SPC+TGN) |
| 6 | scenario_6_spc_all | 78.3% | SPC only (All Days) |
| 7 | scenario_8_spc_7_14 | 73.3% | SPC only (Days 7 & 14) |
| 8 | scenario_9_tgn_7_14 | 73.1% | TGN only (Days 7 & 14) |
| 9 | scenario_7_tgn_all | 69.9% | TGN only (All Days) |
| 10 | scenario_5_day7 | 62.8% | Day 7 only (SPC+TGN) |
## 🔧 API Endpoints
### `GET /variants`
List all available model variants with metadata
### `POST /predict`
Make a prediction using the specified model variant
**Example Request:**
```json
{
"spc_d7": 2.1,
"spc_d14": 4.7,
"spc_d21": 6.4,
"tgn_d7": 1.0,
"tgn_d14": 3.7,
"tgn_d21": 5.3,
"model_variant": "baseline"
}
```
**Example Response:**
```json
{
"prediction": "PPC",
"probabilities": {
"PPC": 0.97,
"no spoilage": 0.02,
"spore spoilage": 0.01
},
"confidence": 0.97,
"variant_used": {
"variant_id": "baseline",
"name": "Baseline (All Features)",
"test_accuracy": 0.9576,
"features": ["SPC_D7", "SPC_D14", "SPC_D21", "TGN_D7", "TGN_D14", "TGN_D21"]
}
}
```
## 📖 Spoilage Classes
| Class | Description |
|-------|-------------|
| **PPC** | Post-Pasteurization Contamination - Bacteria introduced after pasteurization |
| **no spoilage** | No significant spoilage detected |
| **spore spoilage** | Heat-resistant spore-forming bacteria survived pasteurization |
## 🔗 Interactive Documentation
Visit `/docs` for interactive Swagger UI documentation where you can test the API directly.
## 💻 Usage Example
```bash
curl -X POST https://chenhaoq87-milkspoilageclassifier-api-variants.hf.space/predict \
-H "Content-Type: application/json" \
-d '{
"spc_d21": 6.4,
"tgn_d21": 5.3,
"model_variant": "scenario_3_day21"
}'
```
## 🤖 Custom GPT Integration
This API is designed for Custom GPT integration. The GPT will automatically select the best variant based on available data.
See the [Custom GPT Setup Guide](https://huggingface.co/chenhaoq87/MilkSpoilageClassifier/blob/main/docs/CUSTOM_GPT_SETUP_MULTIVARIANT.md) for complete integration instructions.
## 📝 Input Format
All microbial count values should be in **log CFU/mL (base 10)**:
- **SPC** (Standard Plate Count): Total bacterial count
- **TGN** (Total Gram-Negative): Gram-negative bacteria count
- Measured at **Day 7, 14, and 21**
## 🔍 Variant Selection Guide
- **Have all measurements?** → Use `baseline` (best accuracy)
- **Only Day 21 data?** → Use `scenario_3_day21` (nearly as good!)
- **Only Day 14 data?** → Use `scenario_4_day14`
- **Only SPC measurements?** → Use `scenario_6_spc_all`
- **Only TGN measurements?** → Use `scenario_7_tgn_all`
## 📚 Research
Based on predictive modeling for milk spoilage classification using microbial growth patterns.
---
**Model Repository:** [MilkSpoilageClassifier](https://huggingface.co/chenhaoq87/MilkSpoilageClassifier)
|