MyOwnObjectDetectionModel

Object Detection/ObjectDection.py

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+import cv2
+import matplotlib.pyplot as plt
+
+config_file = 'ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt'
+frozen_model = 'frozen_inference_graph.pb'
+model = cv2.dnn_DetectionModel(frozen_model, config_file)
+
+classLabels = []
+file_name = 'labels.txt'
+with open(file_name, 'rt') as fpt:
+    classLabels = fpt.read().rstrip('\n').split('\n')
+
+print(classLabels)
+print(len(classLabels))
+
+model.setInputSize(320, 320)
+model.setInputScale(1.0/127.5)
+model.setInputMean((127.5, 127.5, 127.5))
+model.setInputSwapRB(True)
+
+img = cv2.imread('boy.jpg')
+plt.imshow(img)
+
+ClassIndex, confidence, bbox = model.detect(img, confThreshold=0.5)
+print(ClassIndex)
+
+font_scale = 3
+font = cv2.FONT_HERSHEY_PLAIN
+for ClassInd, conf, boxes in zip(ClassIndex.flatten(), confidence.flatten(), bbox):
+    cv2.rectangle(img, boxes, (255, 0, 0), 2)
+    cv2.putText(img, classLabels[ClassInd-1], (boxes[0]+10, boxes[1]+40), font, fontScale=font_scale, color=(0, 255, 0), thickness=3)
+
+plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
+plt.show()
+
+# Webcam Object Detection
+cap = cv2.VideoCapture('1')
+if not cap.isOpened():
+    cap = cv2.VideoCapture(0)
+if not cap.isOpened():
+    raise IOError("Cannot open video")
+
+font_scale = 3
+font = cv2.FONT_HERSHEY_PLAIN
+
+while True:
+    ret, frame = cap.read()
+
+    ClassIndex, confidence, bbox = model.detect(frame, confThreshold=0.55)
+    print(ClassIndex)
+
+    if (len(ClassIndex) != 0):
+        for ClassInd, conf, boxes in zip(ClassIndex.flatten(), confidence.flatten(), bbox):
+            if (ClassInd <= 80):
+                cv2.rectangle(frame, boxes, (255, 0, 0), 2)
+                cv2.putText(frame, classLabels[ClassInd - 1], (boxes[0] + 10, boxes[1] + 40), font,
+                            fontScale=font_scale, color=(0, 255, 0), thickness=3)
+
+    cv2.imshow('Object Detection Tutorial', frame)
+
+    if cv2.waitKey(2) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()