implemented adas semantic segmentation

CHANGELOG.md

@@ -18,6 +18,7 @@ https://github.com/opencv/cvat/issues/750).
 - REST API to export an annotation task (images + annotations)
 - Datumaro is an experimental framework to build, analyze, debug and visualize datasets for DL algorithms
 - Text Detection Auto Annoation Script in OpenVINO format for version 4
+- Added in OpenVINO Semantic Segmentation for roads
 
 ### Changed
 - page_size parameter for all REST API methods

utils/open_model_zoo/Transportation/semantic-segmentation-adas/interp.py

@@ -0,0 +1,31 @@
+import numpy as np
+from skimage.measure import approximate_polygon, find_contours
+
+import cv2
+
+
+for frame_results in detections:
+    frame_height = frame_results['frame_height']
+    frame_width = frame_results['frame_width']
+    frame_number = frame_results['frame_id']
+    detection = frame_results['detections']
+    detection = detection[0, 0, :, :]
+    width, height = detection.shape
+
+    for i in range(21):
+        zero = np.zeros((width,height),dtype=np.uint8)
+
+        f = float(i)
+        zero = ((detection == f) * 255).astype(np.float32)
+        zero = cv2.resize(zero, dsize=(frame_width, frame_height), interpolation=cv2.INTER_CUBIC)
+
+        contours = find_contours(zero, 0.8)
+
+        for contour in contours:
+            contour = np.flip(contour, axis=1)
+            contour = approximate_polygon(contour, tolerance=2.5)
+            segmentation = contour.tolist()
+            if len(segmentation) < 3:
+                continue
+
+            results.add_polygon(segmentation, i, frame_number)

utils/open_model_zoo/Transportation/semantic-segmentation-adas/mapping.json

@@ -0,0 +1,25 @@
+{
+    "label_map": {
+	    "0": "road",
+	    "1": "sidewalk",
+	    "2": "building",
+	    "3": "wall",
+	    "4": "fence",
+	    "5": "pole",
+	    "6": "traffic light",
+	    "7": "traffic sign",
+	    "8": "vegetation",
+	    "9": "terrain",
+	    "10": "sky",
+	    "11": "person",
+	    "12": "rider",
+	    "13": "car",
+	    "14": "truck",
+	    "15": "bus",
+	    "16": "train",
+	    "17": "motorcycle",
+	    "18": "bicycle",
+	    "19": "ego-vehicle",
+	    "20": "background"
+    }
+}