Add example for incremental learning feature

Signed-off-by: khalid-davis <huangqinkai1@huawei.com>

examples/helmet_detection/README.md

@@ -0,0 +1,192 @@
+# Using Incremental Learning Job in Helmet Detection Scenario
+
+This document introduces how to use incremental learning job in helmet detectioni scenario. Using the incremental learning job, our application can automatically retrains, evaluates, and updates models based on the data generated at the edge.
+
+## Helmet Detection Experiment
+
+### Install Neptune
+
+Follow the [Neptune installation document](/docs/setup/install.md) to install Neptune.
+
+### Prepare Data and Model
+
+Download dataset and model to your node:
+* step 1: download [dataset](https://edgeai-neptune.obs.cn-north-1.myhuaweicloud.com/examples/helmet-detection/dataset.tar.gz)
+```
+mkdir -p /data/helmet_detection
+cd /data/helmet_detection
+tar -zxvf dataset.tar.gz
+```
+* step 2: download [base model](https://edgeai-neptune.obs.cn-north-1.myhuaweicloud.com/examples/helmet-detection/model.tar.gz)
+```
+mkdir /model
+cd /model
+tar -zxvf model.tar.gz
+```
+### Prepare Script
+Download the [scripts](/examples/helmet_detection/training) to the path `code` of your node
+
+
+### Create Incremental Job
+
+Create Dataset
+
+```
+kubectl create -f - <<EOF
+apiVersion: neptune.io/v1alpha1
+kind: Dataset
+metadata:
+  name: incremental-dataset
+  namespace: neptune-test
+spec:
+  url: "/data/helmet_detection/dataset/data.txt"
+  format: "txt"
+  nodeName: "cloud0"
+EOF
+```
+
+Create Initial Model
+
+```
+kubectl create -f - <<EOF
+apiVersion: neptune.io/v1alpha1
+kind: Model
+metadata:
+  name: initial-model
+  namespace: neptune-test
+spec:
+  url : "/model/base_model"
+  format: "ckpt"
+EOF
+```
+
+Create Deploy Model
+
+```
+kubectl create -f - <<EOF
+apiVersion: neptune.io/v1alpha1
+kind: Model
+metadata:
+  name: deploy-model
+  namespace: neptune-test
+spec:
+  url : "/deploy/model.pb"
+  format: "pb"
+EOF
+```
+
+Start The Incremental Learning Job
+
+```
+kubectl create -f - <<EOF
+apiVersion: neptune.io/v1alpha1
+kind: IncrementalLearningJob
+metadata:
+  name: helmet-detection-demo
+  namespace: neptune-test
+spec:
+  initialModel:
+    name: "initial-model"
+  dataset:
+    name: "incremental-dataset"
+    trainProb: 0.8
+  trainSpec:
+    workerSpec:
+      scriptDir: "/code"
+      scriptBootFile: "train.py"
+      frameworkType: "tensorflow"
+      frameworkVersion: "1.15"
+      parameters:
+        - key: "batch_size"
+          value: "32"
+        - key: "epochs"
+          value: "1"
+        - key: "input_shape"
+          value: "352,640"
+        - key: "class_names"
+          value: "person,helmet,helmet-on,helmet-off"
+        - key: "nms_threshold"
+          value: "0.4"
+        - key: "obj_threshold"
+          value: "0.3"
+    trigger:
+      checkPeriodSeconds: 60
+      timer:
+        start: 02:00
+        end: 04:00
+      condition:
+        operator: ">"
+        threshold: 500
+        metric: num_of_samples
+  evalSpec:
+    workerSpec:
+      scriptDir: "/code"
+      scriptBootFile: "eval.py"
+      frameworkType: "tensorflow"
+      frameworkVersion: "1.15"
+      parameters:
+        - key: "input_shape"
+          value: "352,640"
+        - key: "class_names"
+          value: "person,helmet,helmet-on,helmet-off"
+  deploySpec:
+    model:
+      name: "deploy-model"
+    trigger:
+      condition:
+        operator: ">"
+        threshold: 0.1
+        metric: precision_delta
+    nodeName: "cloud0"
+    hardExampleMining:
+      name: "IBT"
+    workerSpec:
+      scriptDir: "/code"
+      scriptBootFile: "inference.py"
+      frameworkType: "tensorflow"
+      frameworkVersion: "1.15"
+      parameters:
+        - key: "input_shape"
+          value: "352,640"
+        - key: "video_url"
+          value: "rtsp://localhost/video"
+        - key: "HE_SAVED_URL" 
+          value: "/he_saved_url"
+  nodeName: "cloud0"
+  outputDir: "/output"
+EOF
+```
+1. The `Dataset` describes data with labels and `HE_SAVED_URL` indicates the address of the deploy container for uploading hard examples. Users will mark label for the hard examples in the address.
+2. Ensure that the path of outputDir in the YAML file exists on your node. This path will be directly mounted to the container.
+
+
+
+### Mock Video Stream for Inference in Edge Side
+
+* step1: install the open source video streaming server [EasyDarwin](https://github.com/EasyDarwin/EasyDarwin/tree/dev).
+* step2: start EasyDarwin server.
+* step3: download [video](https://edgeai-neptune.obs.cn-north-1.myhuaweicloud.com/examples/helmet-detection/video.tar.gz).
+* step4: push a video stream to the url (e.g., `rtsp://localhost/video`) that the inference service can connect.
+
+```
+wget https://github.com/EasyDarwin/EasyDarwin/releases/download/v8.1.0/EasyDarwin-linux-8.1.0-1901141151.tar.gz --no-check-certificate
+tar -zxvf EasyDarwin-linux-8.1.0-1901141151.tar.gz
+cd EasyDarwin-linux-8.1.0-1901141151
+./start.sh
+
+mkdir -p /data/video
+cd /data/video
+tar -zxvf video.tar.gz
+ffmpeg -re -i /data/video/helmet-detection.mp4 -vcodec libx264 -f rtsp rtsp://localhost/video
+```
+
+
+### Check Incremental Job Result
+
+query the service status
+```
+kubectl get incrementallearningjob helmet-detection-demo -n neptune-test
+```
+
+after the job completed, we can view the updated model in the /output directory in cloud0 node
+