How to use TactileNet:

Step 1: Download the dataset locally

git lfs install
git clone https://huggingface.co/datasets/MaiAhmed/TactileNet

Step 2: Install necessary packages

pip install datasets

Step 3: Load the dataset

import os
from datasets import Dataset, Image


def load_data(dataset_path):
    data = []
    for root, dirs, files in os.walk(dataset_path):
        for file in files:
            if file.endswith(".jpg"):
                # Extract class name (e.g., "airplane" from the path)
                class_name = os.path.basename(
                    os.path.dirname(root)
                )  # Gets "airplane" from "train/airplane/Inputs/"

                img_path = os.path.join(root, file)
                txt_path = os.path.join(root, file.replace(".jpg", ".txt"))

                if os.path.exists(txt_path):
                    with open(txt_path, "r") as f:
                        text = f.read().strip()

                    data.append(
                        {
                            "image": img_path,
                            "text": text,
                            "class": class_name,
                        }
                    )
    return data


# Example usage:
dataset_path = "TactileNet/train"  # Replace with your dataset path
data = load_data(dataset_path)

# Convert to Hugging Face Dataset
hf_dataset = Dataset.from_list(data)
hf_dataset = hf_dataset.cast_column("image", Image())  # Auto-convert images

print(hf_dataset[0])  # Check the first sample