image_example1¶
Source code: image_example1.py
Pre-trained model: image_example1.mltk.zip
This provides an example of how to define a classification model that uses the Rock/Paper/Scissors dataset with the ParallelImageGenerator as its data source.
The basic flow for the ML model is:
96x96x1 grayscale image of hand gesture -> ML Model -> [result vector]
Where [result vector] is a 3 element array with each element containing the % probability that the given image is a “rock”, “paper”, or “scissor” hand gesture.
Commands¶
# Do a "dry run" test training of the model
mltk train image_example1-test
# Train the model
mltk train image_example1
# Evaluate the trained model .tflite model
mltk evaluate image_example1 --tflite
# Profile the model in the MVP hardware accelerator simulator
mltk profile image_example1 --accelerator MVP
# Profile the model on a physical development board
mltk profile image_example1 --accelerator MVP --device
# Use the model custom command to dump the augmented samples to ~/.mltk/models/image_example1/datagen_dump
mltk custom image_example1 datagen_dump --count 20
# Directly invoke the model script
python image_example1.py
Model Summary¶
mltk summarize image_example1 --tflite
+-------+-----------------+-------------------+-----------------+-----------------------------------------------------+
| Index | OpCode | Input(s) | Output(s) | Config |
+-------+-----------------+-------------------+-----------------+-----------------------------------------------------+
| 0 | quantize | 96x96x1 (float32) | 96x96x1 (int8) | BuiltinOptionsType=0 |
| 1 | conv_2d | 96x96x1 (int8) | 48x48x24 (int8) | Padding:same stride:2x2 activation:relu |
| | | 3x3x1 (int8) | | |
| | | 24 (int32) | | |
| 2 | average_pool_2d | 48x48x24 (int8) | 24x24x24 (int8) | Padding:valid stride:2x2 filter:2x2 activation:none |
| 3 | conv_2d | 24x24x24 (int8) | 11x11x16 (int8) | Padding:valid stride:2x2 activation:relu |
| | | 3x3x24 (int8) | | |
| | | 16 (int32) | | |
| 4 | conv_2d | 11x11x16 (int8) | 9x9x24 (int8) | Padding:valid stride:1x1 activation:relu |
| | | 3x3x16 (int8) | | |
| | | 24 (int32) | | |
| 5 | average_pool_2d | 9x9x24 (int8) | 4x4x24 (int8) | Padding:valid stride:2x2 filter:2x2 activation:none |
| 6 | reshape | 4x4x24 (int8) | 384 (int8) | BuiltinOptionsType=0 |
| | | 2 (int32) | | |
| 7 | fully_connected | 384 (int8) | 3 (int8) | Activation:none |
| | | 384 (int8) | | |
| | | 3 (int32) | | |
| 8 | softmax | 3 (int8) | 3 (int8) | BuiltinOptionsType=9 |
| 9 | dequantize | 3 (int8) | 3 (float32) | BuiltinOptionsType=0 |
+-------+-----------------+-------------------+-----------------+-----------------------------------------------------+
Total MACs: 1.197 M
Total OPs: 2.561 M
Name: image_example1
Version: 1
Description: Image classifier example for detecting Rock/Paper/Scissors hand gestures in images
Classes: rock, paper, scissor
hash: 31bdc72ea90bfbcfcbe0fccaed749686
date: 2022-04-28T17:33:35.474Z
runtime_memory_size: 71408
samplewise_norm.rescale: 0.0
samplewise_norm.mean_and_std: True
.tflite file size: 15.0kB
Model Profiling Report¶
# Profile on physical EFR32xG24 using MVP accelerator
mltk profile image_example1 --device --accelerator MVP
Profiling Summary
Name: image_example1
Accelerator: MVP
Input Shape: 1x96x96x1
Input Data Type: float32
Output Shape: 1x3
Output Data Type: float32
Flash, Model File Size (bytes): 15.0k
RAM, Runtime Memory Size (bytes): 85.4k
Operation Count: 2.7M
Multiply-Accumulate Count: 1.2M
Layer Count: 10
Unsupported Layer Count: 0
Accelerator Cycle Count: 1.5M
CPU Cycle Count: 970.8k
CPU Utilization (%): 40.6
Clock Rate (hz): 78.0M
Time (s): 30.7m
Ops/s: 87.3M
MACs/s: 39.0M
Inference/s: 32.6
Model Layers
+-------+-----------------+--------+--------+------------+------------+----------+-------------------------+--------------+-----------------------------------------------------+
| Index | OpCode | # Ops | # MACs | Acc Cycles | CPU Cycles | Time (s) | Input Shape | Output Shape | Options |
+-------+-----------------+--------+--------+------------+------------+----------+-------------------------+--------------+-----------------------------------------------------+
| 0 | quantize | 36.9k | 0 | 0 | 314.5k | 4.0m | 1x96x96x1 | 1x96x96x1 | Type=none |
| 1 | conv_2d | 1.2M | 497.7k | 902.9k | 16.1k | 11.4m | 1x96x96x1,24x3x3x1,24 | 1x48x48x24 | Padding:same stride:2x2 activation:relu |
| 2 | average_pool_2d | 69.1k | 0 | 48.5k | 569.2k | 7.6m | 1x48x48x24 | 1x24x24x24 | Padding:valid stride:2x2 filter:2x2 activation:none |
| 3 | conv_2d | 842.2k | 418.2k | 326.6k | 8.0k | 4.2m | 1x24x24x24,16x3x3x24,16 | 1x11x11x16 | Padding:valid stride:2x2 activation:relu |
| 4 | conv_2d | 565.7k | 279.9k | 217.1k | 10.1k | 2.8m | 1x11x11x16,24x3x3x16,24 | 1x9x9x24 | Padding:valid stride:1x1 activation:relu |
| 5 | average_pool_2d | 1.9k | 0 | 1.6k | 43.9k | 540.0u | 1x9x9x24 | 1x4x4x24 | Padding:valid stride:2x2 filter:2x2 activation:none |
| 6 | reshape | 0 | 0 | 0 | 2.4k | 30.0u | 1x4x4x24,2 | 1x384 | Type=none |
| 7 | fully_connected | 2.3k | 1.1k | 1.8k | 2.2k | 30.0u | 1x384,3x384,3 | 1x3 | Activation:none |
| 8 | softmax | 15.0 | 0 | 0 | 3.5k | 60.0u | 1x3 | 1x3 | Type=softmaxoptions |
| 9 | dequantize | 6.0 | 0 | 0 | 1.1k | 0 | 1x3 | 1x3 | Type=none |
+-------+-----------------+--------+--------+------------+------------+----------+-------------------------+--------------+-----------------------------------------------------+
Model Diagram¶
mltk view image_example1 --tflite
