ok that’s good to know and matches the current guide for RetinaNet
arch Backbone for feature extraction. Currently, “resnet”, “vgg”, “darknet”, “googlenet”, “mobilenet_v1”, “mobilenet_v2” and “squeezenet”, “efficientnet_b0” are supported.
However the line given by the NVIDIA notebook for object detection backbones
!ngc registry model list nvidia/tao/pretrained_object_detection:*
ends up listing the following (implying support for object detection):
[{
"accuracyReached": 77.56,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:15:14.015Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "153.7",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 161183816,
"versionId": "vgg19"
},{
"accuracyReached": 77.17,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:14:53.744Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "113.2",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 118655144,
"versionId": "vgg16"
},{
"accuracyReached": 65.13,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:16:58.199Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "6.5",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 6776712,
"versionId": "squeezenet"
},{
"accuracyReached": 77.91,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:12:45.414Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "294.2",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 308488496,
"versionId": "resnet50"
},{
"accuracyReached": 77.04,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:12:15.949Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "170.7",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 178944632,
"versionId": "resnet34"
},{
"accuracyReached": 76.74,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:12:01.650Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "89.0",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 93278448,
"versionId": "resnet18"
},{
"accuracyReached": 77.78,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:13:35.052Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "576.3",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 604328880,
"versionId": "resnet101"
},{
"accuracyReached": 74.38,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:11:51.295Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "38.3",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 40173128,
"versionId": "resnet10"
},{
"accuracyReached": 72.75,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:16:51.593Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "5.0",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 5258048,
"versionId": "mobilenet_v2"
},{
"accuracyReached": 79.5,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:16:42.810Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "26.2",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 27489360,
"versionId": "mobilenet_v1"
},{
"accuracyReached": 77.11,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:17:04.776Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "47.6",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 49958952,
"versionId": "googlenet"
},{
"accuracyReached": 77.11,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:12:16.058Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "26.8",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 28082680,
"versionId": "efficientnet_b1_swish"
},{
"accuracyReached": 77.11,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:11:58.715Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "26.8",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 28082608,
"versionId": "efficientnet_b1_relu"
},{
"accuracyReached": 76.44,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:15:38.311Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "311.7",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 326824240,
"versionId": "darknet53"
},{
"accuracyReached": 77.52,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-08-18T20:16:17.364Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "152.8",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 160242408,
"versionId": "darknet19"
},{
"accuracyReached": 77.1,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-11-23T07:40:58.799Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "28.6",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 29955696,
"versionId": "cspdarknet_tiny"
},{
"accuracyReached": 76.44,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-09-10T00:55:18.313Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "103.0",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 107993624,
"versionId": "cspdarknet53"
},{
"accuracyReached": 77.52,
"batchSize": 1,
"createdByUser": "n90fe0en2gvll5957fel7u75sg",
"createdDate": "2021-09-10T00:55:09.000Z",
"description": "",
"gpuModel": "V100",
"memoryFootprint": "62.9",
"numberOfEpochs": 80,
"status": "UPLOAD_COMPLETE",
"totalFileCount": 1,
"totalSizeInBytes": 65913984,
"versionId": "cspdarknet19"
}]
which includes the efficientnet_b1_relu which did perform well when I used it … so am wondering if the table in the RetinaNet guide would be updated or perhaps I’ve just been lucky to succeed using that b1_relu model in a non-supported role?