This model is trained on a curated dataset of most frequently seen trash items in our college.
Model Details
- Backbone: ResNet50 (ImageNet pre-trained, fine-tuned)
- Classes: 13 trash / recycling / compost categories
- Input size: 224×224 RGB
- Loss: sparse_categorical_crossentropy
- Optimizer: Adam
Dataset
Processed training, validation, and test splits are included in the *_processed directories.
Original dataset: dvk65/TrashTypes
Usage
from huggingface_hub import hf_hub_download
import tensorflow as tf # tensorflow version above 2.20.0
REPO_ID = "dvk65/trash-classifier-resnet50"
FILENAME = "trashclassify_13.keras"
model_path = hf_hub_download(
repo_id=REPO_ID,
filename=FILENAME,
)
model = tf.keras.models.load_model(model_path)
The current target values are:
- apples
- bananas
- bottles
- cans
- cardboard
- cups
- eggshells
- mixed leftover food (labeled as generalcompost)
- wooden coffee stirrers (labeled as mixers)
- oranges (labeled as peels)
- platicbags
- plastic wrappers (labeled as plastics)
- tissue papers
To help with expanding the dataset, feel free to contribute to: https://huggingface.co/datasets/dvk65/TrashTypes
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