Initial commit with project files

CV-App/algorithms/bottle_detection.py

@@ -0,0 +1,69 @@
+"""
+Many thanks to https://github.com/vardanagarwal/Proctoring-AI/blob/master/coco models/tflite mobnetv1 ssd
+"""
+
+
+import cv2
+import numpy as np
+import threading
+from copy import copy
+from time import sleep
+
+from . object_detection import Detector
+from . import Algorithm
+
+
+class BottleDetector(Algorithm):
+    """ Detects objects """
+
+    def __init__(self):
+        """ Init some values and set seed point to None """
+        self.objects = dict()
+        self.detection_image = None
+        self.lock = threading.Lock()
+        self.thread = threading.Thread(target=self._detect, args=[], daemon=True)
+        self.thread.start()
+
+    def process(self, img):
+        """
+        Tries to segment a region around the seed point and calculates a new seed point by finding the segments center
+        """
+        with self.lock:
+            if self.detection_image is None:
+                self.detection_image = np.copy(img)
+        with self.lock:
+            objects = copy(self.objects)
+        h, w, c = img.shape
+
+        if "detection_classes_name" in objects.keys():
+            for i, cls in enumerate(objects["detection_classes_name"]):
+                name = cls["name"]
+                if name in ["bottle", "cup"]:
+                    box = objects["detection_boxes"][i]
+                    score = objects["detection_scores"][i]
+                    y1, x1, y2, x2 = \
+                        max(round(box[0] * h) - 20, 0), round(box[1] * w) - 20 ,\
+                        max(round(box[2] * h) + 20, 0), round(box[3] * w) + 20
+                    if img[y1:y2, x1:x2].size > 0:
+                        img[y1:y2, x1:x2] = cv2.medianBlur(img[y1:y2, x1:x2], 31)
+
+        return img.astype(np.uint8)
+
+    def _detect(self):
+        detector = Detector()
+        while True:
+            with self.lock:
+                img = self.detection_image
+            if img is None:
+                sleep(.033)
+                continue
+            objects = detector.make_inference(img, score_thresh=0.1)
+            with self.lock:
+                self.objects = objects
+                self.detection_image = None
+
+    def mouse_callback(self, event, x, y, flags, param):
+        """ Selects a new seed point"""
+        if event == cv2.EVENT_LBUTTONUP:
+            pass
+