1 from openvino.inference_engine import IECore 2 import numpy as np 3 import time 4 import cv2 as cv 5 6 # 图像识别 7 def ssd_image_demo(): 8 ie = IECore() 9 for device in ie.available_devices: 10 print(device) 11 12 with open('object_detection_classes_coco.txt') as f: 13 labels = [line.strip() for line in f.readlines()] 14 15 model_xml = "ssdv2_graph.xml" 16 model_bin = "ssdv2_graph.bin" 17 18 net = ie.read_network(model=model_xml, weights=model_bin) 19 input_blob = next(iter(net.input_info)) 20 out_blob = next(iter(net.outputs)) 21 22 n, c, h, w = net.input_info[input_blob].input_data.shape #输入BCHW 23 print(n, c, h, w) 24 25 src = cv.imread("001.jpg") 26 image = cv.resize(src, (w, h)) 27 image = image.transpose(2, 0, 1) #HWC->CHW 28 29 exec_net = ie.load_network(network=net, device_name="CPU") 30 res = exec_net.infer(inputs={input_blob:[image]}) 31 32 ih, iw, ic = src.shape 33 res = res[out_blob] #输出(1, 1, N, 7), 34 for obj in res[0][0]: 35 if obj[2] > 0.25: #[image_id, label, conf, x_min, y_min, x_max, y_max] 36 index = int(obj[1])-1 37 print(index) 38 xmin = int(obj[3] * iw) 39 ymin = int(obj[4] * ih) 40 xmax = int(obj[5] * iw) 41 ymax = int(obj[6] * ih) 42 print(labels[index]) 43 cv.rectangle(src, (xmin, ymin), (xmax, ymax), (0, 255, 255), 2, 8) 44 cv.putText(src, labels[index] + str(obj[2]), (xmin, ymin), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1, 8) 45 cv.imshow("SSD Object Detection", src) 46 cv.waitKey(0) 47 48 # 视频识别 49 def ssd_video_demo(): 50 ie = IECore() 51 for device in ie.available_devices: 52 print(device) 53 54 with open('object_detection_classes_coco.txt') as f: 55 labels = [line.strip() for line in f.readlines()] 56 57 model_xml = "ssdv2_graph.xml" 58 model_bin = "ssdv2_graph.bin" 59 60 net = ie.read_network(model=model_xml,weights=model_bin) 61 input_blob = next(iter(net.input_info)) 62 out_blob = next(iter(net.outputs)) 63 64 n, c, h, w = net.input_info[input_blob].input_data.shape 65 print(n, c, h, w) 66 67 cap = cv.VideoCapture("1.mp4") 68 exec_net = ie.load_network(network=net, device_name="CPU") 69 70 while True: 71 ret, frame = cap.read() 72 if ret is not True: 73 break 74 image = cv.resize(frame, (w, h)) 75 image = image.transpose(2, 0, 1) 76 inf_start = time.time() 77 res = exec_net.infer(inputs={input_blob:[image]}) 78 inf_end = time.time() - inf_start 79 print("infer time(ms)：%.3f"%(inf_end*1000)) #推理时间 80 ih, iw, ic = frame.shape 81 res = res[out_blob] 82 for obj in res[0][0]: 83 if obj[2] > 0.25: 84 index = int(obj[1])-1 85 xmin = int(obj[3] * iw) 86 ymin = int(obj[4] * ih) 87 xmax = int(obj[5] * iw) 88 ymax = int(obj[6] * ih) 89 print(labels[index]) 90 cv.rectangle(frame, (xmin, ymin), (xmax, ymax), (0, 255, 255), 2, 8) 91 cv.putText(frame, "infer time(ms): %.3f"%(inf_end*1000), (50, 50), cv.FONT_HERSHEY_SIMPLEX, 1.0, (255, 0, 255), 92 2, 8) 93 cv.putText(frame, labels[index] + str(obj[2]), (xmin, ymin), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1, 8) 94 cv.imshow("SSD Object Detection", frame) 95 c = cv.waitKey(1) 96 if c == 27: 97 break 98 99 100 if __name__ == "__main__": 101 ssd_video_demo()