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ImageAIRealTimeWebCamPerformance.py
# load HL detection model from imageAI
# open camera with openCV, analyze frame by frame
# draw a red frame around the detected object
# display FPS, resize image to 1/4 to improve performance
from imageai.Detection.Custom import CustomObjectDetection
import os
import cv2
import time
detector = CustomObjectDetection()
detector.setModelTypeAsYOLOv3()
detector.setModelPath("hololens-ex-60--loss-2.76.h5")
detector.setJsonPath("detection_config.json")
detector.loadModel()
# init camera
execution_path = os.getcwd()
camera = cv2.VideoCapture(0)
camera.set(cv2.CAP_PROP_FRAME_WIDTH,640)
camera.set(cv2.CAP_PROP_FRAME_HEIGHT,480)
while True:
# FPS process
start_time = time.time()
# Grab a single frame of video
ret, frame = camera.read()
fast_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
detected_image, detections = detector.detectObjectsFromImage(input_image=fast_frame, input_type="array", output_type="array")
for detection in detections:
# frame for the detected object
(x1, y1, x2, y2) = detection["box_points"]
x1 *= 4
y1 *= 4
x2 *= 4
y2 *= 4
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
# Draw a label with the detected object type below the frame
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, detection["name"], (x1 + 6, y1 - 6), font, 1.0, (255, 255, 255), 1)
#display FPS
fpsInfo = "FPS: " + str(1.0 / (time.time() - start_time)) # FPS = 1 / time to process loop
print(fpsInfo)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, fpsInfo, (10, 20), font, 0.4, (255, 255, 255), 1)
# Display the resulting image
cv2.imshow('Video', frame)
# Hit 'q' on the keyboard to quit!
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()
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