Handwritten-Digit-GAN AmirhosseinHonardoust · COMPLETED
A PyTorch implementation of a Deep Convolutional GAN (DCGAN) trained on MNIST. Includes training scripts, generator & discriminator models, random sample generation, latent space interpolation, and loss curve visualization to create realistic handwritten digit images.
github.com/AmirhosseinHonardoust/Handwritten-Digit-GAN · ★ 29 · Forks 0 · Size 19.1 MB
SUMMARY
Technologies 8
Scored 8
Observed 8
Practices 6
Evidence 10
Skips 0
COVERAGE
Analyzed 22 files · 12 commits · 0 API calls
TECHNOLOGIES & DEPTH
TOML LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
2 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
12 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
Poetry BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth 62
2 files · PRODUCTION
pytest TESTING Depth 41
2 files · TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2025-09-12
Last commit 2026-09-06
Active months 2
Commits 12