File size: 1,644 Bytes
5e4b609 | 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 | # 🧪 Test Samples
Welcome! This folder contains sample images you can use to test CleanEye's garbage detection capabilities.
## 📸 Sample Images
We've included 5 diverse test images:
1. **sample_1_bins.jpg** - Garbage and recycle bins
2. **sample_2_bags.jpg** - Black garbage bags
3. **sample_3_pile.jpg** - Large pile of garbage
4. **sample_4_street.jpg** - Street waste scenario
5. **sample_5_plastic.jpg** - Plastic waste accumulation
## 🚀 How to Test
### Option 1: Web Interface (Recommended)
```bash
python start.py
```
Then select option 1 to launch the Streamlit dashboard, and upload any sample image.
### Option 2: Command Line
```bash
# Using the detect script
python code/detect_pro.py --source test_samples/sample_1_bins.jpg
# View all detections
python code/app.py
```
### Option 3: HuggingFace Space
Visit: https://huggingface.co/spaces/AlBaraa63/cleaneye-garbage-detection
Upload any of these samples directly in your browser!
## 🎯 What You'll See
CleanEye will detect and classify:
- 🗑️ **garbage** - General garbage items
- 👜 **garbage_bag** - Plastic waste bags
- 📦 **c** - Containers
- ♻️ **waste** - Waste materials
- 🚮 **trash** - Trash items
- 📊 **0** - General waste category
Each detection includes:
- Bounding box highlighting
- Confidence score
- Color-coded classification
- Real-time statistics
## 💡 Tips
- Try uploading multiple images in sequence
- Test with different lighting conditions
- Compare detection accuracy across samples
- Use the video mode for webcam testing
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**Happy Testing!** 🎉
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