pelee-coco

## Use Case and High-Level Description

The Pelee is a Real-Time Object Detection System on Mobile Devices based on Single Shot Detection approach. The model is implemented using the Caffe* framework and trained on Common Objects in Context (COCO) dataset. For details about this model, check out the repository.

## Specification

Metric Value
Type Detection
GFLOPs 1,290
MParams 5.98
Source framework Caffe*

## Accuracy

Metric Value
coco_precision 21.9761%

See here.

## Input

### Original model

Image, name - data, shape - 1, 3, 304, 304, format is B, C, H, W, where:

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

Channel order is BGR. Mean values - [103.94, 116.78, 123.68], Scale - 58.8235.

### Converted model

Image, name - data, shape - 1, 3, 304, 304, format is B, C, H, W, where:

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

Channel order is BGR.

## Output

### Original model

The array of detection summary info, name - detection_out, shape - 1, 1, 200, 7 in the format 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 batch
• label - predicted class ID in range [1, 80], mapping to class names provided in <omz_dir>/data/dataset_classes/coco_80cl.txt file
• 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])

### Converted model

The array of detection summary info, name - detection_out, shape - 1, 1, 200, 7 in the format 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 batch
• label - predicted class ID in range [1, 80], mapping to class names provided in <omz_dir>/data/dataset_classes/coco_80cl_bkgr.txt file
• 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])

You can download models and if necessary convert them into Inference Engine format using the Model Downloader and other automation tools as shown in the examples below.