Update Docker images name for multiedgeinference components.

Signed-off-by: Vittorio Cozzolino <vittorio.cozzolino@huawei.com>

examples/build_image.sh

@@ -61,11 +61,11 @@ IMAGE_TAG=${IMAGE_TAG:-v0.5.0}
 EXAMPLE_REPO_PREFIX=${IMAGE_REPO}/sedna-example-
 
 dockerfiles_multiedgeinference=(
-multi-edge-inference-feature-extraction.Dockerfile
-# multi-edge-inference-gpu-feature-extraction.Dockerfile
-# multi-edge-inference-gpu-videoanalytics.Dockerfile
-multi-edge-inference-reid.Dockerfile
-multi-edge-inference-videoanalytics.Dockerfile
+multi-edge-inference-pedestrian-tracking-feature-extraction.Dockerfile
+# multi-edge-inference-pedestrian-tracking-gpu-feature-extraction.Dockerfile
+# multi-edge-inference-pedestrian-tracking-gpu-videoanalytics.Dockerfile
+multi-edge-inference-pedestrian-tracking-reid.Dockerfile
+multi-edge-inference-pedestrian-tracking-videoanalytics.Dockerfile
 )
 
 dockerfiles_federated_learning=(

examples/multiedgeinference/pedestrian_tracking/README.md

@@ -32,14 +32,14 @@ The image below shows the system architecture and its simplified workflow:
 - Available for CPU only.
 - Folder with specific implementation `examples/multiedgeinference/pedestrian_tracking/reid`.
 - Component specs in `lib/sedna/core/multi_edge_inference/components/reid.py`.
-- Defined by the Dockerfile `multi-edge-inference-reid.Dockerfile`.
+- Defined by the Dockerfile `multi-edge-inference-pedestrian-tracking-reid.Dockerfile`.
 
 **Feature Extraction Service**: it performs the extraction of the features necessary for the ReID step.
 
 - Available for CPU and GPU.
 - Folder with specific implementation details `examples/multiedgeinference/pedestrian_tracking/feature_extraction`.
 - Component specs in `lib/sedna/core/multi_edge_inference/components/feature_extraction.py`.
-- Defined by the Dockerfile `multi-edge-inference-feature-extraction.Dockerfile` or `multi-edge-inference-gpu-feature-extraction.Dockerfile`.
+- Defined by the Dockerfile `multi-edge-inference-pedestrian-tracking-feature-extraction.Dockerfile` or `multi-edge-inference-pedestrian-tracking-gpu-feature-extraction.Dockerfile`.
 - It loads the model defined by the CRD in the YAML file `yaml/models/model_m3l.yaml`.
 
 **VideoAnalytics Job**: it performs tracking of objects (pedestrians) in a video.
@@ -48,7 +48,7 @@ The image below shows the system architecture and its simplified workflow:
 - Folder with specific implementation details `examples/multiedgeinference/pedestrian_tracking/detection`.
 - AI model code in `examples/multiedgeinference/detection/estimator/bytetracker.py`.
 - Component specs in `lib/sedna/core/multi_edge_inference/components/detection.py`.
-- Defined by the Dockerfile `multi-edge-inference-videoanalytics.Dockerfile` or `multi-edge-inference-gpu-videoanalytics.Dockerfile`.
+- Defined by the Dockerfile `multi-edge-inference-pedestrian-tracking-videoanalytics.Dockerfile` or `multi-edge-inference-pedestrian-tracking-gpu-videoanalytics.Dockerfile`.
 - It loads the model defined by the CRD in the YAML file `yaml/models/model_detection.yaml`.
 
 # Build Phase

examples/multiedgeinference/pedestrian_tracking/yaml/feature-extraction-service.yaml

@@ -18,7 +18,7 @@ spec:
       nodeSelector:
         node-role.kubernetes.io/master: ''
       containers:
-      - image: registry-cbu.huawei.com/kubeedge/sedna-example-multi-edge-inference-feature-extraction:v0.5.0
+      - image: kubeedge/sedna-example-multi-edge-inference-pedestrian-tracking-feature-extraction:v0.5.0
         imagePullPolicy: Always
         name:  feature-extraction
         env:

examples/multiedgeinference/pedestrian_tracking/yaml/reid-job.yaml

@@ -1,4 +1,4 @@
-apiVersion: sedna.io/v1alpha1
+    apiVersion: sedna.io/v1alpha1
 kind: ReidJob
 metadata:
   name: reid
@@ -10,7 +10,7 @@ spec:
       nodeSelector:
         node-role.kubernetes.io/master: ''
       containers:
-        - image: registry-cbu.huawei.com/kubeedge/sedna-example-multi-edge-inference-reid:v0.5.0
+        - image: kubeedge/sedna-example-multi-edge-inference-pedestrian-tracking-reid:v0.5.0
           name:  reid
           imagePullPolicy: Always
           env:

examples/multiedgeinference/pedestrian_tracking/yaml/video-analytics-job.yaml

@@ -12,7 +12,7 @@ spec:
       nodeSelector:
         node-role.kubernetes.io/master: ''
       containers:
-        - image: registry-cbu.huawei.com/kubeedge/sedna-example-multi-edge-inference-videoanalytics:sase
+        - image: kubeedge/sedna-example-multi-edge-inference-pedestrian-tracking-videoanalytics:v0.5.0
           imagePullPolicy: Always
           name:  detection
           env: