Added the OpenCv Model

Object Detection/ObjectDection.py

@@ -0,0 +1,82 @@
+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()