Irgenija/sign_language_resnet50

Description

This model with transfer learning is trained to recognise Sign Language. The model was trained on the basis of ResNet50. The dataset was used for training https://huggingface.co/datasets/aliciiavs/sign_language_image_dataset

In model.py file you can find class of custom model. For using model you need download model.py, import from it class CustomResNetModel, create an example of this class and load and apply model weight from file sign_language_resnet50.pth Model's metrics: loss: 0.5739429252889922 accuracy: 0.901717

Example of code

import torch
from huggingface_hub import hf_hub_download

from model import CustomResNetModel

device = "cuda" if torch.cuda.is_available() else "cpu"
model = CustomResNetModel(num_classes=24)
weight_path = hf_hub_download(
    repo_id="Irgenija/sign_language_resnet50", 
    filename="sign_language_resnet50.pth",
)
if cls.device == "cpu":
    checkpoint = torch.load(
        weight_path, map_location=torch.device("cpu")
    )
else:
    checkpoint = torch.load(weight_path)
model.load_state_dict(checkpoint)
model = model.to(device) # Optional
model.eval()