{"adoption": {"forks": 1230, "observed_at": "2026-08-28T04:10:12.257312+00:00", "stars": 8048}, "canonical_url": "https://ross.abutalabs.com/products/paddlegan", "card": {"archived": false, "artifact_type": "library", "description": "PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer,  Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.", "domain": ["deep-learning", "computer-vision", "image-processing", "artificial-intelligence"], "enriched": true, "function": ["image-processing", "video-processing", "machine-learning", "deep-learning"], "health_score": 20, "homepage": null, "language": "Python", "license": "Apache-2.0", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["PaddlePaddle/PaddleGAN"], "name": "PaddlePaddle/PaddleGAN", "platform": ["python"], "pushed_at": "2024-07-03T15:05:24+00:00", "repo": "PaddlePaddle/PaddleGAN", "stars": 8048, "tags": ["gan", "style-transfer", "super-resolution", "motion-transfer", "face-editing", "image-restoration", "paddlepaddle", "wav2lip", "photo2cartoon", "video", "linux", "gpu"], "topics": ["gan", "cyclegan", "pix2pix", "super-resolution", "image-generation", "image-editing", "motion-transfer", "photo2cartoon", "psgan", "resolution", "wav2lip", "gpen", "first-order-motion-model", "realsr", "edvr", "basicvsrplusplus", "stylegan2", "animeganv2"], "urls": [], "use_cases": ["animate a photo to make it talk with wav2lip", "transfer motion from a video to a still image", "upscale low-resolution images and videos", "convert a portrait photo to cartoon style", "restore and enhance old or damaged photos", "edit faces in images with stylegan", "train and deploy custom GAN models"], "what_it_is": "PaddleGAN is a Python library providing high-performance implementations of classic and state-of-the-art Generative Adversarial Networks built on PaddlePaddle. It includes ready-to-use applications such as first-order motion transfer, Wav2Lip lip-syncing, image restoration, photo-to-cartoon, face editing, and image/video super-resolution.", "when_to_avoid": ["you need PyTorch or TensorFlow instead of PaddlePaddle", "you need a general-purpose image editing tool rather than GAN research models", "you require frequent updates or active community support"], "when_to_choose": ["you want prebuilt GAN applications like lip-syncing, motion transfer, or super-resolution", "your stack is already on PaddlePaddle", "you need both training and inference for GAN models in Python"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/paddlegan", "repo": "PaddlePaddle/PaddleGAN", "role": "main", "score": 23}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:10:12.257312+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T17:31:24.704673+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "bdf30cbb88ec61a3514145b12f01973440c196a5e454a731976f37d12dff6489", "fetched_at": "2026-08-28T04:10:12.257312+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/PaddleGAN"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 8}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": [], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2267, "days_push": 791, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 23, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}