{"id":24446268,"url":"https://github.com/kentaroy47/ssd.objectdetection.pytorch","last_synced_at":"2025-10-10T08:30:43.116Z","repository":{"id":104244875,"uuid":"207447646","full_name":"kentaroy47/SSD.objectdetection.pytorch","owner":"kentaroy47","description":"Library for training and testing object detection for Pytorch (ssd, retinanet)","archived":false,"fork":false,"pushed_at":"2019-12-02T23:53:23.000Z","size":99946,"stargazers_count":8,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-03T18:09:04.659Z","etag":null,"topics":["fpn","inference","objectdetection","pytorch","retinanet","ssd","train-ssd","yolo"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ObjectDetection.Pytorch\n![teaser](https://github.com/kentaroy47/ObjectDetection.Pytorch/blob/master/imgs/1.png)\n\nThis repo is an object detection library for pytorch (single stage detectors).\n\n**RetinaNet Architecture**\n\nVOCmAP: train VOC07+12 test VOC07\n\n|*backbone*|*resolution*|*VOCmAP*    |*COCOmAP*|*Inference[ms]*|*model*|\n|:------:|:------------:|:----------:|:-------:|:-------------:|:-----:|\n|VGG16   |300           |79.5        |         |               |[here](https://github.com/kentaroy47/ObjectDetection.Pytorch/releases/download/ssdvgg200/ssd300_200.pth)|\n|resnet18|300           |76.5        |         |               |       |\n|resnet50|300           |80.5        |         |               |       |\n|resnet101|300           |           |         |               |       |\n|resnet18|600           |            |         |               |       |\n|resnet50|600           |            |         |               |       |\n|resnet101|600           |           |         |               |       |\n\n## To start off\nrequirements: cv2, pandas. plz install.\n\nclone the repo.\n```\ngit clone https://github.com/kentaroy47/ObjectDetection.Pytorch.git\n```\n\nDownload PASCALVOC2007 dataset and extract.\n```\nwget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar\n```\n\nDownload reduced FC vgg weights and place in weights folder.\n```\nmkdir weights\ncd weights\nwget https://s3.amazonaws.com/amdegroot-models/vgg16_reducedfc.pth\n```\n\n## Train SSD Models\nrun train_ssd.ipynb\n\nto run inference, try inference.ipynb.\n\nthe trained SSD model is here (still underfitting..)\nhttps://github.com/kentaroy47/ObjectDetection.Pytorch/releases/download/ssdvgg200/ssd300_200.pth\n\n## Train YOLO Models\nrun yolo.ipynb (TBD)\n\n## Train Faster RCNN Models\nrun frcnn.ipynb (TBD)\n\n## Test models\nrun `eval.ipynb`\n\n# Test results for ssd\n\nPascal VOC 2007 test set.\n\n### SSD-300\nModel:\nhttps://github.com/kentaroy47/ObjectDetection.Pytorch/releases/download/ssdvgg200/ssd300_200.pth\n\nMean AP = 0.7959\n\n~~~~~~~~\nResults:\n0.842\n0.850\n0.784\n0.736\n0.518\n0.891\n0.888\n0.902\n0.634\n0.832\n0.793\n0.873\n0.899\n0.862\n0.815\n0.521\n0.798\n0.815\n0.885\n0.780\n0.796\n~~~~~~~~\n\n### RetinaNet-300 Resnet18\nMean AP = 0.7279\n~~~~~~~~\nResults:\n0.759\n0.814\n0.725\n0.661\n0.373\n0.807\n0.836\n0.847\n0.508\n0.759\n0.741\n0.816\n0.848\n0.813\n0.743\n0.420\n0.695\n0.803\n0.859\n0.731\n0.728\n~~~~~~~~\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkentaroy47%2Fssd.objectdetection.pytorch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkentaroy47%2Fssd.objectdetection.pytorch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkentaroy47%2Fssd.objectdetection.pytorch/lists"}