feat: fall-detect initialization

Merge pull request #14 from bhavikapanara/primary-fall-detect

.github/workflows/pythonpackage.yml

@@ -0,0 +1,77 @@
+name: Python package
+
+on: [push, pull_request]
+
+jobs:
+  build:
+    name: Build Job
+
+    runs-on: ubuntu-20.04
+    strategy:
+      max-parallel: 4
+      matrix:
+        python-version: [3.7, 3.8]
+
+    steps:
+    - uses: actions/checkout@v1
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v1
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install python package locally
+      run: |
+        python3 -m pip install --upgrade pip
+        pip3 install --editable src
+    - name: Lint with flake8
+      run: |
+        pip3 install flake8
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Test with pytest
+      env:
+        ARCH: "linux/amd64"
+        TAG_SUFFIX: "amd64"
+      run: |
+        pip3 install pytest
+        pwd
+        ls -al
+        echo GITHUB_WORKSPACE=${GITHUB_WORKSPACE}
+        echo "ARCH=${ARCH}"
+        ${GITHUB_WORKSPACE}/install_requirements.sh
+        ${GITHUB_WORKSPACE}/tests/run-tests.sh
+        
+        
+  release:
+    name: Release Job
+    needs: [build]
+    if: github.ref == 'refs/heads/master' && github.event_name == 'push'
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v1
+    - name: Install Node.js 12
+      uses: actions/setup-node@v1
+      with:
+        node-version: 12.x
+    - name: Install Python 3
+      uses: actions/setup-python@v1
+      with:
+        python-version: '3.x'
+    - name: Install Semantic Release Tool
+      run: |
+            npm install --save-dev semantic-release
+            npm install --save-dev @semantic-release/commit-analyzer
+            npm install --save-dev @semantic-release/git
+            npm install --save-dev @semantic-release/release-notes-generator
+            npm install --save-dev @semantic-release/github
+            npm install --save-dev @semantic-release/changelog
+            npm install --save-dev @semantic-release/exec
+    - name: Run Semantic Release
+      run: npx semantic-release
+      env:
+        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        NPM_TOKEN: ${{ secrets.NPM_TOKEN }}
+        CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+    - name: Semantic release completed
+      run: echo Semantic release flow completed

.github/workflows/pythonpublish.yml

@@ -0,0 +1,28 @@
+name: Upload Python Package
+
+on:
+  release:
+    types: [created]
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v1
+    - name: Set up Python
+      uses: actions/setup-python@v1
+      with:
+        python-version: '3.x'
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install setuptools wheel twine
+    - name: Build and publish
+      env:
+        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+      run: |
+        cp README.md src/
+        cd src
+        python setup.py sdist bdist_wheel
+        twine upload dist/*

.releaserc

@@ -0,0 +1,30 @@
+{
+    "branch": "master",
+    "plugins": [
+        "@semantic-release/commit-analyzer",
+        "@semantic-release/release-notes-generator",
+        [
+            "@semantic-release/changelog",
+            {
+                "changelogFile": "CHANGELOG.md",
+                "changelogTitle": "# Semantic Versioning Changelog"
+            }
+        ],
+        [
+            "@semantic-release/exec",
+            {
+                "prepareCmd": "./build/prepare-semantic-release.sh ${nextRelease.version}"
+            }
+        ],
+        [
+            "@semantic-release/git",
+            {
+                "assets": [
+                    "CHANGELOG.md",
+                    "src/setup.cfg"
+                ]
+            }
+        ],
+        "@semantic-release/github",
+    ]
+}

README.md

@@ -4,12 +4,12 @@ _This repo is the new home of the fall detection model used in Ambianic Edge. We
 
 # TODO
 
-- [ ] Standalone Python ML library for people fall detection based on Tensorflow and [PoseNet 2.0](https://github.com/tensorflow/tfjs-models/tree/master/posenet).
+- [x] Standalone Python ML library for people fall detection based on Tensorflow and [PoseNet 2.0](https://github.com/tensorflow/tfjs-models/tree/master/posenet).
 - [ ] Python source code and wheel package published on PyPi 
-- [ ] Jupyter Notebook to interactively test and experiement with the model
-- [ ] CI & test suite
-- [ ] Training and testing data sets
-- [ ] Third party ML models used as building blocks
+- [x] Jupyter Notebook to interactively test and experiement with the model
+- [x] CI & test suite
+- [x] Training and testing data sets
+- [x] Third party ML models used as building blocks
 
 # Project motivation
 
@@ -32,6 +32,32 @@ In the current design we use a combination of the [PoseNet 2.0](https://github.c
 
 [![Fall Detection AI flow](https://user-images.githubusercontent.com/2234901/112545190-ea89d380-8d85-11eb-8e2c-7a6b104d159e.png)](https://drive.google.com/file/d/1sr2OcEWsGzoxJb4PwCIXOuEo7a5ubAxG/view?usp=sharing)
 
+# Experiment
+
+Experiment with the fall-detection module using simple script, jupyter-notebook or command line input(CLI) by feeding 2 or 3 images. The input images should be spaced about 1 second apart.
+
+###### Run a Python Script
+
+```
+python3 demo-fall-detection.py
+```
+
+###### Run a `Demo.ipynb` jupyter-notebook for the experiment
+
+###### Execute the below command for CLI usage
+
+To test fall-detection using the CLI for 2 images:
+
+```
+python3 demo-fall-detection-cmd.py --image_1 Images/fall_img_1.png --image_2 Images/fall_img_2.png
+```
+
+To test fall-detection using the CLI for 3 images:
+
+```
+python3 demo-fall-detection-cmd.py --image_1 Images/fall_img_1.png --image_2 Images/fall_img_2.png --image_3 Images/fall_img_3.png
+```
+
 # Limitations
 
 Based on testing and user feedback we are aware of the following limitations for the Fall Detection algorithm:

ai_models/pose_labels.txt

@@ -0,0 +1 @@
+1	FALL

demo-fall-detection-cmd.py

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+import argparse
+from pathlib import Path
+from PIL import Image
+from fall_prediction import Fall_prediction
+import numpy as np
+import json
+import time
+import yaml
+
+class JsonEncoder(json.JSONEncoder):
+    def default(self, obj):
+        if isinstance(obj, np.integer):
+            return int(obj)
+        if isinstance(obj, np.floating):
+            return float(obj)
+        if isinstance(obj, np.ndarray):
+            return obj.tolist()
+
+        return super(JsonEncoder, self).default(obj)
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--image_1", type=Path, help='Path to the First Image', required=True)
+parser.add_argument("--image_2", type=Path, help='Path to the Second Image', required=True)
+parser.add_argument("--image_3", type=Path, help='Path to the Third Image')
+
+p = parser.parse_args()
+img1 = Image.open(p.image_1)
+img2 = Image.open(p.image_2)
+img3 = Image.open(p.image_3) if p.image_3 else None
+
+response = Fall_prediction(img1, img2, img3)
+
+if response:
+
+    print("There is", response['category'])
+    print("Confidence :", response['confidence'])
+    print("Angle : ", response['angle'])
+    print("Keypoint_corr :", response['keypoint_corr'])
+
+    time_str = time.strftime("%Y%m%d-%H%M%S")
+    json_str = json.dumps(response, cls=JsonEncoder)
+
+    with open(f"tmp/{time_str}.yaml","w",) as file:
+        yaml.dump(json.loads(json_str), file)
+else:
+     print("There is no fall detetcion...")
+

demo-fall-detection.py

@@ -0,0 +1,16 @@
+from PIL import Image
+from fall_prediction import Fall_prediction
+
+img1 = Image.open("Images/fall_img_1.png")
+img2 = Image.open("Images/fall_img_2.png")
+img3 = Image.open("Images/fall_img_3.png")
+
+response = Fall_prediction(img1, img2, img3)
+
+if response:
+    print("There is", response['category'])
+    print("Confidence :", response['confidence'])
+    print("Angle : ", response['angle'])
+    print("Keypoint_corr :", response['keypoint_corr'])
+else:
+     print("There is no fall detetcion...")

fall_prediction.py

@@ -0,0 +1,83 @@
+import os
+import time
+
+from src.pipeline.fall_detect import FallDetector
+
+
+def _fall_detect_config():
+
+    _dir = os.path.dirname(os.path.abspath(__file__))
+    _good_tflite_model = os.path.join(
+        _dir,
+        'ai_models/posenet_mobilenet_v1_100_257x257_multi_kpt_stripped.tflite'
+        )
+    _good_edgetpu_model = os.path.join(
+        _dir,
+        'ai_models/posenet_mobilenet_v1_075_721_1281_quant_decoder_edgetpu.tflite'
+        )
+    _good_labels = 'ai_models/pose_labels.txt'
+    config = {
+        'model': {
+            'tflite': _good_tflite_model,
+            'edgetpu': _good_edgetpu_model,
+            },
+        'labels': _good_labels,
+        'top_k': 3,
+        'confidence_threshold': 0.6,
+    }
+    return config
+
+
+def Fall_prediction(img_1,img_2,img_3=None):
+
+    config = _fall_detect_config()
+    result = None
+
+    fall_detector = FallDetector(**config)
+
+    def process_response(response):
+        nonlocal result
+        for res in response:
+            result = res['inference_result']
+
+    process_response(fall_detector.process_sample(image=img_1))
+
+    time.sleep(fall_detector.min_time_between_frames)
+
+    process_response(fall_detector.process_sample(image=img_2))
+
+    if len(result) == 1:
+        category = result[0]['label']
+        confidence = result[0]['confidence']
+        angle = result[0]['leaning_angle']
+        keypoint_corr = result[0]['keypoint_corr']
+
+        dict_res = {}
+        dict_res["category"] = category
+        dict_res["confidence"] = confidence
+        dict_res["angle"] = angle
+        dict_res["keypoint_corr"] = keypoint_corr
+        return dict_res
+
+    else:
+
+        if img_3:
+
+            time.sleep(fall_detector.min_time_between_frames)
+            process_response(fall_detector.process_sample(image=img_3))
+
+            if len(result) == 1:
+
+                category = result[0]['label']
+                confidence = result[0]['confidence']
+                angle = result[0]['leaning_angle']
+                keypoint_corr = result[0]['keypoint_corr']
+
+                dict_res = {}
+                dict_res["category"] = category
+                dict_res["confidence"] = confidence
+                dict_res["angle"] = angle
+                dict_res["keypoint_corr"] = keypoint_corr
+                return dict_res
+
+    return None

install_requirements.sh

@@ -0,0 +1,56 @@
+#!/bin/bash
+
+echo "Installing Ambianic dependencies"
+
+# exit bash script on error
+set -e
+
+# verbose mode
+set -x
+
+# update apt-get and install sudo
+apt-get update -y && apt-get install -y sudo
+
+# check if python3 is installed
+if python3 --version
+then
+  echo "python3 is already installed."
+else
+  # install python3 and pip3 which are not available by default on slim buster
+  echo "python3 is not available from the parent image. Installing python3 now."
+  sudo apt-get install -y python3 && apt-get install -y python3-pip
+fi
+
+# install numpy native lib
+sudo apt-get install -y python3-numpy
+sudo apt-get install -y libjpeg-dev zlib1g-dev
+
+
+# install python dependencies
+python3 -m pip install --upgrade pip
+pip3 --version
+pip3 install -r requirements.txt
+
+
+
+echo "Installing tflite for x86 CPU"
+if python3 --version | grep -q 3.8
+then
+  pip3 install --force-reinstall https://github.com/google-coral/pycoral/releases/download/v1.0.1/tflite_runtime-2.5.0-cp38-cp38-linux_x86_64.whl
+else
+  pip3 install https://dl.google.com/coral/python/tflite_runtime-1.14.0-cp37-cp37m-linux_x86_64.whl
+fi
+
+pip3 list
+pip3 show tflite-runtime
+
+
+
+# [Cleanup]
+sudo apt-get -y autoremove
+
+# remove apt-get cache
+sudo  rm -rf /var/lib/apt/lists/*
+
+# This is run automatically on Debian and Ubuntu, but just in case
+sudo apt-get clean