---
license: apache-2.0
tags:
  - image-classification
  - plastic-waste
  - recycling
  - convnext
  - timm
  - pytorch
pipeline_tag: image-classification
---

# Plastic Waste Classifier

Classifies plastic waste images into **6 resin types** for recycling sorting.

Built for [Hackniche 4.0](https://hackniche.in/).

## Performance (Test Set, 5-view TTA)

| Metric | Value |
|---|---|
| Accuracy | **92.02%** |
| Macro F1 | **0.9077** |
| Best Val F1 | 0.9177 |

## Model Details

| Property | Value |
|---|---|
| Base Model | `convnext_base.fb_in22k_ft_in1k_384` |
| Pretraining | ImageNet-22k then ImageNet-1k (86.8% top-1) |
| Input Size | 384 x 384 px |
| Parameters | ~88M |
| Fine-tuning | Full LLRD + EMA |

## Classes

| Label | Code | Material | Recyclable |
|---|---|---|---|
| PET  | #1 | Polyethylene Terephthalate | Yes |
| HDPE | #2 | High-Density Polyethylene  | Yes |
| LDPE | #4 | Low-Density Polyethylene   | Yes |
| PP   | #5 | Polypropylene              | Yes |
| PS   | #6 | Polystyrene                | No  |
| Other| #7 | Mixed / Unknown            | Depends |

## Quick Start

```python
import torch, timm, numpy as np
import albumentations as A
from albumentations.pytorch import ToTensorV2
from huggingface_hub import hf_hub_download
from PIL import Image

weights = hf_hub_download('Vansh180/plastic-waste-classifier', 'plastic_classifier_best.pt')
model = timm.create_model('convnext_base.fb_in22k_ft_in1k_384', pretrained=False, num_classes=6)
model.load_state_dict(torch.load(weights, map_location='cpu'))
model.eval()

transform = A.Compose([
    A.Resize(416, 416), A.CenterCrop(384, 384),
    A.Normalize([0.485,0.456,0.406],[0.229,0.224,0.225]), ToTensorV2(),
])
CLASS_NAMES = ['HDPE','LDPE','Other','PET','PP','PS']
img = np.array(Image.open('plastic.jpg').convert('RGB'))
t = transform(image=img)['image'].unsqueeze(0)
with torch.no_grad():
    probs = torch.softmax(model(t), dim=1)[0]
print(CLASS_NAMES[probs.argmax()], f'{probs.max():.1%}')
```

## License
Apache 2.0