Terriao/OpenPCQA

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54 of your 99 findings came from Repobility's proprietary detections. ✓ Repobility tags below mark them.

Upstream (GitHub) caused delay on this scan — not Repobility.

GitHub API rate-limited (HTTP 403) — preflight skipped, fell back to direct git clone.
Clone from GitHub took 169.23s for a 204.7 MB repo slow.
Repobility's analysis ran in 2.51s after the clone landed.

https://github.com/Terriao/OpenPCQA · scanned 2026-06-05 17:47 UTC (4 days, 21 hours ago) · 10 languages

258 raw signals (92 security + 166 graph) 11/13 scanners ran 29th percentile · Python · small (2-20K LoC) System graph score 97 (lower by 38)

File as issue Image

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 4 days, 21 hours ago · v2 · 82 actionable findings from 2 signal sources. 93 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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77.8% cov · 49 findings

Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	40.0	0.15	6.00
`security_score`	100.0	0.25	25.00
`testing_score`	34.0	0.20	6.80
`documentation_score`	65.0	0.15	9.75
`practices_score`	30.0	0.15	4.50
`code_quality`	67.0	0.10	6.70
Overall		1.00	58.8

security_score may be inflated — optional security scanners were skipped on this fast scan

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 23 Medium 3 Low 18 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 33 System graph 49 Crowd 0 Layer: Quality 42 Software 34 Api 1 Frontend 1 Security 3 Cicd 1

Exclude dismissed / FP Exclude test files

All 666 nodes from the latest scan, grouped by kind. Each node is a unit the engine identified (file, function, endpoint, table…). Most users won't need this view — it's primarily for debugging the engine's graph extraction or for AI agents that want to enumerate the project structure.

Label	Layer	Status	Path
`get_config`	software	healthy	`ResSCNN/ResSCNN-tf/config.py:46`
`lossname2dirname`	software	healthy	`ResSCNN/ResSCNN-tf/split_data.py:13`
`main`	software	healthy	`ResSCNN/ResSCNN-tf/main.py:10`
`__init__`	software	healthy	`ResSCNN/ResSCNN-tf/models/Res_Models.py:9`
`call`	software	dead	`ResSCNN/ResSCNN-tf/models/Res_Models.py:38`
`__init__`	software	healthy	`ResSCNN/ResSCNN-tf/models/Res_Blocks.py:5`
`call`	software	dead	`ResSCNN/ResSCNN-tf/models/Res_Blocks.py:16`
`__init__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/transforms.py:17`
`__call__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/transforms.py:21`
`__init__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/utils.py:7`
`__call__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/utils.py:13`
`normalize_point_coordinates`	software	healthy	`ResSCNN/ResSCNN-tf/lib/utils.py:20`
`compute_voxel_grid`	software	healthy	`ResSCNN/ResSCNN-tf/lib/utils.py:33`
`M`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:19`
`sample_random_trans`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:23`
`__init__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:112`
`__getitem__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:59`
`apply_transform`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:97`
`__call__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:103`
`__len__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:137`
`get_dataset`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:140`
`__init__`	software	healthy	`ResSCNN/ResSCNN-tf/lib/trainer.py:13`
`train`	software	healthy	`ResSCNN/ResSCNN-tf/lib/trainer.py:49`
`_test_epoch`	software	healthy	`ResSCNN/ResSCNN-tf/lib/trainer.py:98`
`save_model_weight`	software	healthy	`ResSCNN/ResSCNN-tf/lib/trainer.py:120`
`add_argument_group`	software	healthy	`ResSCNN/ResSCNN-ms/config.py:7`
`str2bool`	software	dead	`ResSCNN/ResSCNN-ms/config.py:13`
`get_config`	software	healthy	`ResSCNN/ResSCNN-ms/config.py:77`
`main`	software	healthy	`ResSCNN/ResSCNN-ms/main.py:13`
`__init__`	software	healthy	`ResSCNN/ResSCNN-ms/models/Res_blocks.py:5`
`construct`	software	dead	`ResSCNN/ResSCNN-ms/models/Res_blocks.py:16`
`__init__`	software	healthy	`ResSCNN/ResSCNN-ms/models/Res_Models.py:7`
`construct`	software	dead	`ResSCNN/ResSCNN-ms/models/Res_Models.py:36`
`__init__`	software	healthy	`ResSCNN/ResSCNN-ms/lib/transforms.py:17`
`__call__`	software	healthy	`ResSCNN/ResSCNN-ms/lib/transforms.py:21`
`fill`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:12`
`uniform`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:19`
`zeros`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:22`
`repeat`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:25`
`clamp`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:32`
`sigmoid`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:44`
`expand`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:48`
`size_to_ms_tensor`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:50`
`max`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:63`
`linspace`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:84`
`pad`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:93`
`_call_ms_api`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:105`
`max_pool2d`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:182`
`copy`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:155`
`chunk`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py:161`

Showing first 50 of this kind. Full payload available via the JSON button at the top of the page.

Label	Layer	Status	Path
`ResSCNN`	software	healthy	`ResSCNN/ResSCNN-tf/models/Res_Models.py:6`
`BasicBlock`	software	healthy	`ResSCNN/ResSCNN-tf/models/Res_Blocks.py:4`
`Compose`	software	healthy	`ResSCNN/ResSCNN-tf/lib/transforms.py:4`
`Jitter`	software	healthy	`ResSCNN/ResSCNN-tf/lib/transforms.py:15`
`Printl`	software	healthy	`ResSCNN/ResSCNN-tf/lib/utils.py:6`
`DataGenerator`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:31`
`ResDataset`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py:111`
`Trainer`	software	healthy	`ResSCNN/ResSCNN-tf/lib/trainer.py:12`
`BasicBlock`	software	healthy	`ResSCNN/ResSCNN-ms/models/Res_blocks.py:4`
`ResSCNN`	software	healthy	`ResSCNN/ResSCNN-ms/models/Res_Models.py:5`
`Compose`	software	healthy	`ResSCNN/ResSCNN-ms/lib/transforms.py:4`
`Jitter`	software	healthy	`ResSCNN/ResSCNN-ms/lib/transforms.py:15`
`Printl`	software	healthy	`ResSCNN/ResSCNN-ms/lib/utils.py:6`
`ResDataset`	software	healthy	`ResSCNN/ResSCNN-ms/lib/data_loaders.py:98`
`MyWithLossCell`	software	healthy	`ResSCNN/ResSCNN-ms/lib/trainer.py:13`
`Trainer`	software	healthy	`ResSCNN/ResSCNN-ms/lib/trainer.py:31`
`ResNet`	software	healthy	`VQA_PC/TensorFlow/test/ResNet_mean_with_fast.py:11`
`VideoDataset_NR_image_with_fast_features`	software	healthy	`VQA_PC/TensorFlow/test/data_loader.py:7`
`ResNet`	software	healthy	`VQA_PC/TensorFlow/train/ResNet_mean_with_fast.py:11`
`VideoDataset_NR_image_with_fast_features`	software	healthy	`VQA_PC/TensorFlow/train/data_loader.py:7`
`BasicBlock`	software	healthy	`VQA_PC/mindspore/test/ResNet_mean_with_fast.py:25`
`Bottleneck`	software	healthy	`VQA_PC/mindspore/test/ResNet_mean_with_fast.py:64`
`ResNet`	software	healthy	`VQA_PC/mindspore/test/ResNet_mean_with_fast.py:106`
`VideoDataset_NR_image_with_fast_features`	software	healthy	`VQA_PC/mindspore/test/data_loader.py:13`
`BasicBlock`	software	healthy	`VQA_PC/mindspore/train/ResNet_mean_with_fast.py:25`
`Bottleneck`	software	healthy	`VQA_PC/mindspore/train/ResNet_mean_with_fast.py:64`
`ResNet`	software	healthy	`VQA_PC/mindspore/train/ResNet_mean_with_fast.py:106`
`MyWithLossCell`	software	healthy	`VQA_PC/mindspore/train/train_WPC.py:33`
`MyWithLossCell`	software	healthy	`VQA_PC/mindspore/train/train_SJTU.py:33`
`VideoDataset_NR_image_with_fast_features`	software	healthy	`VQA_PC/mindspore/train/data_loader.py:12`
`ClipWrapper`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py:13`
`RandomTemporalClip`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py:29`
`RandomCropWithStrides`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py:65`
`DenseTemporalClip`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py:133`
`DenseSpatialCrop`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py:158`
`DenseSpatialCrop_collate`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py:192`
`RandomHorizontalFlipClip`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py:226`
`RandomPatchSelection`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py:247`
`MyWithLossCell`	software	healthy	`PQA-Net/PQA-Net-mindspore/TrainModelDTLQ.py:28`
`Trainer`	software	healthy	`PQA-Net/PQA-Net-mindspore/TrainModelDTLQ.py:47`
`ImageQualityDatasetLQFull`	software	healthy	`PQA-Net/PQA-Net-mindspore/ImageQualityDatasetLQSixSeperate.…`
`ImageQualityDatasetLQSixSeperate`	software	healthy	`PQA-Net/PQA-Net-mindspore/ImageQualityDatasetLQSixSeperate.…`
`GdnFunction`	software	healthy	`PQA-Net/PQA-Net-mindspore/Gdn.py:13`
`Gdn`	software	healthy	`PQA-Net/PQA-Net-mindspore/Gdn.py:48`
`MyWithLossCell`	software	healthy	`PQA-Net/PQA-Net-mindspore/TrainModelLQ.py:26`
`Trainer`	software	healthy	`PQA-Net/PQA-Net-mindspore/TrainModelLQ.py:56`
`MyView`	software	healthy	`PQA-Net/PQA-Net-mindspore/MeonLQ.py:17`
`MyCat`	software	healthy	`PQA-Net/PQA-Net-mindspore/MeonLQ.py:25`
`MeonNoDT`	software	healthy	`PQA-Net/PQA-Net-mindspore/MeonLQ.py:33`
`MeonNoDTSize`	software	healthy	`PQA-Net/PQA-Net-mindspore/MeonLQ.py:86`

Showing first 50 of this kind. Full payload available via the JSON button at the top of the page.

Label	Layer	Status	Path
`README.md`	software	healthy	`README.md`
`readme.md`	software	healthy	`ResSCNN/readme.md`
`config.py`	software	healthy	`ResSCNN/ResSCNN-tf/config.py`
`Readme.md`	software	healthy	`ResSCNN/ResSCNN-tf/Readme.md`
`split_data.py`	software	healthy	`ResSCNN/ResSCNN-tf/split_data.py`
`main.py`	software	healthy	`ResSCNN/ResSCNN-tf/main.py`
`Res_Models.py`	software	healthy	`ResSCNN/ResSCNN-tf/models/Res_Models.py`
`Res_Blocks.py`	software	healthy	`ResSCNN/ResSCNN-tf/models/Res_Blocks.py`
`transforms.py`	software	healthy	`ResSCNN/ResSCNN-tf/lib/transforms.py`
`utils.py`	software	healthy	`ResSCNN/ResSCNN-tf/lib/utils.py`
`data_loaders.py`	software	healthy	`ResSCNN/ResSCNN-tf/lib/data_loaders.py`
`trainer.py`	software	healthy	`ResSCNN/ResSCNN-tf/lib/trainer.py`
`README.md`	software	healthy	`ResSCNN/ResSCNN-ms/README.md`
`config.py`	software	healthy	`ResSCNN/ResSCNN-ms/config.py`
`split_data.py`	software	warning	`ResSCNN/ResSCNN-ms/split_data.py`
`main.py`	software	healthy	`ResSCNN/ResSCNN-ms/main.py`
`Res_blocks.py`	software	healthy	`ResSCNN/ResSCNN-ms/models/Res_blocks.py`
`Res_Models.py`	software	healthy	`ResSCNN/ResSCNN-ms/models/Res_Models.py`
`transforms.py`	software	healthy	`ResSCNN/ResSCNN-ms/lib/transforms.py`
`ms_tools.py`	software	healthy	`ResSCNN/ResSCNN-ms/lib/ms_tools.py`
`utils.py`	software	healthy	`ResSCNN/ResSCNN-ms/lib/utils.py`
`data_loaders.py`	software	healthy	`ResSCNN/ResSCNN-ms/lib/data_loaders.py`
`trainer.py`	software	healthy	`ResSCNN/ResSCNN-ms/lib/trainer.py`
`README.md`	software	healthy	`VQA_PC/README.md`
`ResNet_mean_with_fast.py`	software	healthy	`VQA_PC/TensorFlow/test/ResNet_mean_with_fast.py`
`data_loader.py`	software	healthy	`VQA_PC/TensorFlow/test/data_loader.py`
`test.py`	software	healthy	`VQA_PC/TensorFlow/test/test.py`
`ResNet_mean_with_fast.py`	software	healthy	`VQA_PC/TensorFlow/train/ResNet_mean_with_fast.py`
`train_WPC.py`	software	healthy	`VQA_PC/TensorFlow/train/train_WPC.py`
`train_SJTU.py`	software	healthy	`VQA_PC/TensorFlow/train/train_SJTU.py`
`data_loader.py`	software	healthy	`VQA_PC/TensorFlow/train/data_loader.py`
`ResNet_mean_with_fast.py`	software	healthy	`VQA_PC/mindspore/test/ResNet_mean_with_fast.py`
`data_loader.py`	software	healthy	`VQA_PC/mindspore/test/data_loader.py`
`test.py`	software	healthy	`VQA_PC/mindspore/test/test.py`
`ResNet_mean_with_fast.py`	software	healthy	`VQA_PC/mindspore/train/ResNet_mean_with_fast.py`
`train_WPC.py`	software	healthy	`VQA_PC/mindspore/train/train_WPC.py`
`train_SJTU.py`	software	healthy	`VQA_PC/mindspore/train/train_SJTU.py`
`data_loader.py`	software	healthy	`VQA_PC/mindspore/train/data_loader.py`
`README.md`	software	healthy	`PQA-Net/README.md`
`MainDTLQ.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/MainDTLQ.py`
`README.md`	software	healthy	`PQA-Net/PQA-Net-mindspore/README.md`
`VideoTransforms.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/VideoTransforms.py`
`TrainModelDTLQ.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/TrainModelDTLQ.py`
`ImageQualityDatasetLQSixSeperate.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/ImageQualityDatasetLQSixSeperate.…`
`MainLQ.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/MainLQ.py`
`Gdn.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/Gdn.py`
`torch2ms_tools.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/torch2ms_tools.py`
`TrainModelLQ.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/TrainModelLQ.py`
`MeonLQ.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/MeonLQ.py`
`ImageQualityDatasetLQSeperate.py`	software	healthy	`PQA-Net/PQA-Net-mindspore/ImageQualityDatasetLQSeperate.py`

Showing first 50 of this kind. Full payload available via the JSON button at the top of the page.

Label	Layer	Status	Path
`ResSCNN`	software	healthy	`ResSCNN`
`ResSCNN-tf`	software	healthy	`ResSCNN/ResSCNN-tf`
`models`	software	healthy	`ResSCNN/ResSCNN-tf/models`
`lib`	software	healthy	`ResSCNN/ResSCNN-tf/lib`
`ResSCNN-ms`	software	healthy	`ResSCNN/ResSCNN-ms`
`models`	software	healthy	`ResSCNN/ResSCNN-ms/models`
`lib`	software	healthy	`ResSCNN/ResSCNN-ms/lib`
`VQA_PC`	software	healthy	`VQA_PC`
`TensorFlow`	software	healthy	`VQA_PC/TensorFlow`
`test`	software	healthy	`VQA_PC/TensorFlow/test`
`train`	software	healthy	`VQA_PC/TensorFlow/train`
`mindspore`	software	healthy	`VQA_PC/mindspore`
`test`	software	healthy	`VQA_PC/mindspore/test`
`train`	software	healthy	`VQA_PC/mindspore/train`
`PQA-Net`	software	healthy	`PQA-Net`
`PQA-Net-mindspore`	software	healthy	`PQA-Net/PQA-Net-mindspore`
`dataset`	software	healthy	`PQA-Net/PQA-Net-mindspore/dataset`
`PQA-Net-tf`	software	healthy	`PQA-Net/PQA-Net-tf`
`IT-PCQA`	software	healthy	`IT-PCQA`
`MindSpore`	software	healthy	`IT-PCQA/MindSpore`
`network`	software	healthy	`IT-PCQA/MindSpore/network`
`TensorFlow`	software	healthy	`IT-PCQA/TensorFlow`
`network`	software	healthy	`IT-PCQA/TensorFlow/network`
`PRL-GQA`	software	healthy	`PRL-GQA`
`MindSpore`	software	healthy	`PRL-GQA/MindSpore`
`TensorFlow`	software	healthy	`PRL-GQA/TensorFlow`
`PyTorch`	software	healthy	`PRL-GQA/PyTorch`

Label	Layer	Status	Path
`repobility-clone-trzpx0xh`	software	healthy	`/tmp/repobility-clone-trzpx0xh`

Label	Layer	Status	Path
`gpu (detected)`	hardware	healthy	`ResSCNN/ResSCNN-tf/main.py`

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Terriao/OpenPCQA

Complete repo analysis

function 50+

class 50+

file 50+

directory 27

repo 1

gpu 1