assignment-bp-roma-cherniak-2026 0.1.0

make my own ASL clasifier on A , B , C , D , nothing latters using Pytorch and OpenCV

MY Simple ASL project with OpenCV

Installation - pip install assignment_bp_roma_cherniak_2026

Quick Start

Predict from image file

from asl_classifier import load_model, predict
from PIL import Image

model = load_model()
image = Image.open("hand.jpg")
label, confidence = predict(model, image)
print(f"Prediction: {label} ({confidence}%)")

Try it live with your webcam

from asl_classifier import load_model, run_webcam

model = load_model()
run_webcam(model)  # press Q to quit

API Reference

load_model(weights_path=None)

Loads the ASL classifier model with pretrained weights.

predict(model, image)

Runs inference on a single PIL image.

• model — loaded model from load_model()
• image — PIL Image object

run_webcam(model)

Opens webcam and runs live prediction in real time.

• model — loaded model from load_model()
• Press Q to quit

Net

PyTorch nn.Module class implementing a 4-layer CNN for ASL classification.

• Input: RGB image of any size (resized to 128x128 internally)
• Output: class probabilities for 5 signs

Evaluation Proposal

My primary metrics for evaluating the model's performance were validation accuracy during training, as well as the model's real-world ability to recognize these signs in practice. While the results demonstrated promising progress, the model is far from optimal and requires further refinement and improvement.