The "efficientdet-d1-tf" model is one of the EfficientDet models designed to perform object detection. This model was pretrained in TensorFlow*. All the EfficientDet models have been pretrained on the MSCOCO* image database. For details about this family of models, check out the Google AutoML repository.
Metric | Value |
---|---|
Type | Object detection |
GFLOPs | 6.1 |
MParams | 6.6 |
Source framework | TensorFlow* |
Metric | Converted model |
---|---|
COCO* mAP (0.5:0.05:0.95) | 37.54% |
Image, name - image_arrays
, shape - [1x640x640x3]
, format is [BxHxWxC]
, where:
B
- batch sizeH
- heightW
- widthC
- channelChannel order is RGB
.
Image, name - image_arrays/placeholder_port_0
, shape - [1x3x640x640]
, format is [BxCxHxW]
, where:
B
- batch sizeC
- channelH
- heightW
- widthChannel order is BGR
.
The array of summary detection information, name: detections
, shape: [1, N, 7], where N is the number of detected bounding boxes. For each detection, the description has the format: [image_id
, y_min
, x_min
, y_max
, x_max
, confidence
, label
], where:
image_id
- ID of the image in the batchx_min
, y_min
) - coordinates of the top left bounding box cornerx_max
, y_max
) - coordinates of the bottom right bounding box cornerconfidence
- confidence for the predicted classlabel
- predicted class ID, starting from 1The array of summary detection information, name: detections
, shape: [1, 1, N, 7], where N is the number of detected bounding boxes. For each detection, the description has the format: [image_id
, label
, conf
, x_min
, y_min
, x_max
, y_max
], where:
image_id
- ID of the image in the batchlabel
- predicted class ID, starting from 0conf
- confidence for the predicted classx_min
, y_min
) - coordinates of the top left bounding box corner (coordinates stored in normalized format, in range [0, 1])x_max
, y_max
) - coordinates of the bottom right bounding box corner (coordinates stored in normalized format, in range [0, 1])The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in APACHE-2.0-TF-AutoML.txt.