definition.yaml

benchmark:
  COCO 2017 Validation:
    mAP: 0.234
description: SSD MobileNet v1 is a object detection network, that localizes and identifies
  objects in an input image. This is a TF Lite quantized version that takes a 300x300
  input image and outputs detections for this image. This model is converted from
  FP32 to INT8 using post-training quantization.
license:
- Apache-2.0
network:
  file_size_bytes: 7311392
  filename: ssd_mobilenet_v1.tflite
  framework: TensorFlow Lite
  hash:
    algorithm: sha1
    value: fef68428bd439b70eb983b57d6a342871fa0deaa
  provenance: https://arxiv.org/abs/1512.02325
network_parameters:
  input_nodes:
  - description: A resized and normalized input image.
    example_input:
      path: models/object_detection/ssd_mobilenet_v1/tflite_int8/testing_input/tfl.quantize
    name: tfl.quantize
    shape:
    - 1
    - 300
    - 300
    - 3
  output_nodes:
  - description: The y1, x1, y2, x2 coordinates of the bounding boxes for each detection
    name: TFLite_Detection_PostProcess:01
    shape: []
    test_output_path: models/object_detection/ssd_mobilenet_v1/tflite_int8/testing_output/TFLite_Detection_PostProcess:01
  - description: The class of each detection
    name: TFLite_Detection_PostProcess:02
    shape: []
    test_output_path: models/object_detection/ssd_mobilenet_v1/tflite_int8/testing_output/TFLite_Detection_PostProcess:02
  - description: The probability score for each classification
    name: TFLite_Detection_PostProcess:03
    shape: []
    test_output_path: models/object_detection/ssd_mobilenet_v1/tflite_int8/testing_output/TFLite_Detection_PostProcess:03
  - description: A vector containing a number corresponding to the number of detections
    name: TFLite_Detection_PostProcess:04
    shape: []
    test_output_path: models/object_detection/ssd_mobilenet_v1/tflite_int8/testing_output/TFLite_Detection_PostProcess:04
operators:
  TensorFlow Lite:
  - CONCATENATION
  - CONV_2D
  - CUSTOM
  - DEPTHWISE_CONV_2D
  - DEQUANTIZE
  - LOGISTIC
  - QUANTIZE
  - RELU6
  - RESHAPE
paper: https://arxiv.org/abs/1512.02325