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i3d-rgb-tf

Use Case and High-Level Description

The i3d-rgb-tf is a model for video classification, based on paper "Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset". This model use RGB input stream and trained on Kinetics-400* dataset . Additionally, this model has initialize values from Inception v1 model pretrained on ImageNet* dataset.

Originally redistributed as a checkpoint file, was converted to frozen graph.

Conversion

  1. Clone or download original repository: 
    git clone https://github.com/deepmind/kinetics-i3d.git
  2. (Optional) Checkout the commit that the conversion was tested on: 
    git checkout 0667e88
  3. Install prerequisites, tested with: 
    tensorflow==1.11
tensorflow-probability==0.4.0
dm-sonnet==1.26
  4. Copy script to root directory of original repository and run it: 
    python freeze.py

Specification

Metric Value
Type Action recognition
GFLOPs 278.981
MParams 12.69
Source framework TensorFlow*

Accuracy

Accuracy validations performed on validation part of Kinetics-400* dataset. Subset consists of 400 randomly chosen videos from this dataset.

Metric Converted Model Converted Model (subset 400)
Top 1 65.96% 67.0%
Top 5 86.01% 88.7%

Input

Original Model

Video clip, name - Placeholder, shape - 1,79,224,224,3, format is B,D,H,W,C, where:

  • B - batch size
  • D - duration of input clip
  • H - height
  • W - width
  • C - channel

Channel order is RGB. Mean value - 127.5, scale value - 127.5.

Converted Model

Video clip, name - Placeholder, shape - 1,79,3,224,224, format is B,D,C,H,W, where:

  • B - batch size
  • D - duration of input clip
  • C - channel
  • H - height
  • W - width

Channel order is RGB.

Output

Original Model

Action classifier according to Kinetics-400* action classes, name - Softmax, shape - 1,400, format is B,C, where:

  • B - batch size
  • C - predicted probabilities for each class in [0, 1] range

Converted Model

Action classifier according to Kinetics-400* action classes, name - Softmax, shape - 1,400, format is B,C, where:

  • B - batch size
  • C - predicted probabilities for each class in [0, 1] range

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.txt.