OpenCV3.4.2 Dnn Object Detection with TensorFlow Model

取り敢えず、プログラムはこちらです。

object__detection_cv3__cam.py
''' object__detection_cv3__cam.py Sample from https://github.com/opencv/opencv/wiki/TensorFlow-Object-Detection-API Created on 2018/09/13 @author: nishi ''' import cv2 import os import numpy as np import sys import math def rotate_fuc(rot,p0,p1): ''' 図形の回転を行います。 [cosθ -sinθ] [x] [sinθ cosθ] [y] ''' rad=math.radians(rot) cos0=math.cos(rad) sin0=math.sin(rad) a = np.array([ [cos0,(-1)*sin0], [sin0,cos0]]) ''' Numpy.dot で、行列の積を計算します。 ''' p0=np.dot(a,p0) p1=np.dot(a,p1) return(p0,p1) ''' USBカメラオープン ''' if False: video = cv2.VideoCapture(0) # Exit if video not opened. if not video.isOpened(): print("Could not open video") sys.exit() ''' Web CAM(Mjpeg-streamer) オープン ''' if True: #URL="http://200.36.58.250/mjpg/video.mjpg?resolution=320x240" URL="http://200.36.58.250/mjpg/video.mjpg?resolution=640x480" video = cv2.VideoCapture(URL) # Exit if video not opened. if not video.isOpened(): print("Could not open Web CAM") sys.exit() BASE_DIR='Object_detection_cv3' if True: MODEL_NAME = 'ssd_mobilenet_v1_coco_2017_11_17' PATH_TO_LABELS = os.path.join(BASE_DIR, 'ssd_mobilenet_v1_coco_2017_11_17.pbtxt') if True: MODEL_NAME = 'ssd_mobilenet_v2_coco_2018_03_29' PATH_TO_LABELS = os.path.join(BASE_DIR,'ssd_mobilenet_v2_coco_2018_03_29.pbtxt') PATH_TO_CKPT = os.path.join(BASE_DIR,MODEL_NAME,'frozen_inference_graph.pb') print('PATH_TO_CKPT=',PATH_TO_CKPT) print('PATH_TO_LABELS=',PATH_TO_LABELS) #cvNet = cv.dnn.readNetFromTensorflow('frozen_inference_graph.pb', 'graph.pbtxt') cvNet = cv2.dnn.readNetFromTensorflow(PATH_TO_CKPT, PATH_TO_LABELS) while True: #image = Image.open(image_path) # Read first frame. ok, image_np = video.read() if not ok: print('Cannot read video file') sys.exit() print('image_np.shape=',image_np.shape) rows = image_np.shape[0] cols = image_np.shape[1] print('rows=',rows,',cols=',cols) ''' Doc from https://www.pyimagesearch.com/2017/11/06/deep-learning-opencvs-blobfromimage-works/ https://docs.opencv.org/trunk/d6/d0f/group__dnn.html#ga33d1b39b53a891e98a654fdeabba22eb ''' #cvNet.setInput(cv2.dnn.blobFromImage(image_np, size=(300, 300), swapRB=True, crop=False)) cvNet.setInput(cv2.dnn.blobFromImage(image_np, size=(cols, rows), swapRB=True, crop=False)) #W=640 #H=480 #cvNet.setInput(cv2.dnn.blobFromImage(image_np, 1.0, (W, H),(104.0, 177.0, 123.0))) #cvNet.setInput(cv2.dnn.blobFromImage(image_np, size=(rows, cols), swapRB=True, crop=False)) cvOut = cvNet.forward() #print('cvOut.shape=',cvOut.shape) cnt=cvOut.shape[2] print('cnt=',cnt) det = cvOut[0,0,:,:] #print('det.shape=',det.shape) col_num = 2 det_reverse = det[np.argsort(det[:, col_num])[::-1]] max_cnt=5 #for detection in cvOut[0,0,:,:]: for detection in det_reverse[:,:]: score = float(detection[2]) if score > 0.25: #print('detection[0]=',detection[0]) classes =int(detection[1]) print('classes=',classes,',score=',score,',detection[3:]=',detection[3:]) if True: left = x0 = detection[3] * cols top= y0 = detection[4] * rows right = x1 = detection[5] * cols bottom = y1 = detection[6] * rows # 矩形の中心　O1 を求める centerX= int((x0 + x1)/2) centerY= int((y0 + y1)/2) # 中心点を描画 cv2.drawMarker(image_np, (centerX,centerY), (255, 0, 255), markerType=cv2.MARKER_SQUARE, markerSize=5) text = "{}".format(classes) cv2.putText(image_np, text, (centerX + 5, centerY+5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 255), 2) if False: left = x0 = detection[3] * cols top= y0 = detection[4] * rows right = x1 = detection[5] * cols bottom = y1 = detection[6] * rows # 矩形の中心　O1 を求める centerX= (x0 + x1)/2 centerY= (y0 + y1)/2 # 中心点を描画 cv2.drawMarker(image_np, (int(centerX),int(centerY)), (255, 0, 255), markerType=cv2.MARKER_SQUARE, markerSize=5) left = centerX - (x0 + x1)/2 * 0.022 top = centerY - (y0 + y1)/2 * 0.12 right = centerX + (x0 + x1)/2 * 0.022 bottom = centerY + (y0 + y1)/2 * 0.12 if False: # 90度回転 left = x0 = detection[3] * cols top= y0 = detection[4] * rows right = x1 = detection[5] * cols bottom = y1 = detection[6] * rows # オリジナルを描画 #cv2.rectangle(image_np, (int(left), int(top)), (int(right), int(bottom)), (23, 230, 210), thickness=2) # 矩形の中心　O1 を求める centerX= (x0 + x1)/2 centerY= (y0 + y1)/2 # 中心点を描画 cv2.drawMarker(image_np, (int(centerX),int(centerY)), (255, 0, 255), markerType=cv2.MARKER_SQUARE, markerSize=5) # 中心 O1 からの相対位置を求める x0r = x0 - centerX y0r = y0 - centerY x1r = x1 - centerX y1r = y1 - centerY p0 = np.array([x0r,y0r]) p1 = np.array([x1r,y1r]) # 矩形の回転 90 (p0,p1)=rotate_fuc(90,p0,p1) # Z(0,0) からの位置に戻す left = p0[0] + centerX top = p0[1] + centerY right = p1[0] + centerX bottom = p1[1] + centerY cv2.rectangle(image_np, (int(left), int(top)), (int(right), int(bottom)), (23, 230, 210), thickness=1) max_cnt=max_cnt-1 if(max_cnt <0): break cv2.imshow('img',image_np) #---------------- # プログラムの終了は、 q を入力してください。 #---------------- if cv2.waitKey(1) & 0xFF == ord('q'): break video.release() cv2.destroyAllWindows()