Use Case and High-Level Description

The ssd_resnet50_v1_fpn_coco model is a SSD FPN object detection architecture based on ResNet-50. The model has been trained from the Common Objects in Context (COCO) image dataset. For details see the repository and paper.

Specification

Accuracy

Input

Original model

Image, name - image_tensor, shape - [1x640x640x3], format -[BxHxWxC] where:

• B - batch size
• H - height
• W - width
• C - channel

Expected color order - RGB.

Converted model

Image, name - image_tensor, shape - [1x3x640x640], format is [BxCxHxW] where:

• B - batch size
• C - channel
• H - height
• W - width

Expected color order - BGR.

Output

NOTE output format changes after Model Optimizer conversion. To find detailed explanation of changes, go to Model Optimizer development guide

Original model

1. Classifier, name - detection_classes, contains predicted bounding boxes classes in range [1, 91]. The model was trained on Microsoft* COCO dataset version with 90 categories of object.
2. Probability, name - detection_scores, contains probability of detected bounding boxes.
3. Detection box, name - detection_boxes, contains detection boxes coordinates in format [y_min, x_min, y_max, x_max], where (x_min, y_min) are coordinates top left corner, (x_max, y_max) are coordinates right bottom corner. Coordinates are rescaled to input image size.
4. Detections number, name - num_detections, contains the number of predicted detection boxes.

Converted model

The array of summary detection information, name - detection_out, shape - [1x1xNx7], 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 batch
• label - predicted class ID
• conf - confidence for the predicted class
• (x_min, y_min) - coordinates of the top left bounding box corner (coordinates are in normalized format, in range [0, 1])
• (x_max, y_max) - coordinates of the bottom right bounding box corner (coordinates are in normalized format, in range [0, 1])

Legal Information

The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in APACHE-2.0-TensorFlow.txt.