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Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,196 @@ import os import cv2 import numpy as np from skimage.feature import blob_dog, blob_log, blob_doh from math import sqrt from time import time from multiprocessing import Pool, Queue def GetDiff(img0,img1,thresh_diff_pix): img_diff=img0-img1 img_abs=np.fabs(img_diff) img_abs_3c=np.sum(img_abs,axis=2)/3/255 lower_th=thresh_diff_pix img_range=cv2.inRange(img_abs_3c,thresh_diff_pix,1) return img_range def find_lines(params): fid, fblobs, seeds, ishape = params cnt = 0 for seed in seeds: for i in range(fid - 2, 0, -1): if i not in fblobs or fid - 2 - i > 10: break ifblobs = fblobs[i] imark = [0] * len(ifblobs) for j, ifblob in enumerate(ifblobs): cnt += 1 if seed[-1][1] <= int(ifblob[0]) or abs(seed[-1][0] - int(ifblob[1])) >= ishape[1] // 10 or \ (seed[-1][1] - int(ifblob[0])) >= ishape[0] // 10: continue if imark[j] != 0: continue dv = [seed[-2][0] - seed[-1][0], seed[-2][1] - seed[-1][1]] dv_norm = np.linalg.norm(np.array(dv)) idv = [seed[-1][0] - int(ifblob[1]), seed[-1][1] - int(ifblob[0])] idv_norm = np.linalg.norm(np.array(idv)) cosangle = np.array(dv).dot(np.array(idv)) / (dv_norm * idv_norm) angle = np.arccos(cosangle) # 0.26 is about 15 degree if angle < 0.26: seed.append((int(ifblob[1]), int(ifblob[0]))) imark[j] = 1 break print (len(seeds), cnt) return seeds class DropDetect: def __init__(self): self.back_sum=None self.back_avg=None self.last_img=[] self.img_counter=0 self.thresh_diff_pix=0.1 self.list_mask_area=[] self.list_mask_area.append(object) self.fblobs = {} def Pre(self,img): self.FeedBackGround(img) def FeedBackGround(self,img): if self.back_sum==None: self.back_sum=img.astype(np.float32) self.back_sum+=img.astype(np.float32) self.img_counter+=1 self.back_avg=self.back_sum/self.img_counter def SubBack(self,img): h,w,u=img.shape if self.img_counter<100: return np.zeros() def GetBackGound(self,source,num_frames): vc=cv2.VideoCapture(source) res,img=vc.read() # temp img = cv2.resize(img, (img.shape[1] // 4, img.shape[0] // 4)) img_sum=img.astype(np.float32) counter=1 while True: res,img=vc.read() if res==False: break # temp img = cv2.resize(img, (img.shape[1] // 4, img.shape[0] // 4)) img_sum+=img counter+=1 if num_frames<0: continue elif counter>num_frames: break back_avg=img_sum/counter return back_avg def GetDiff(self,img, fid): img_float=img.astype(np.float32) diff_avg=GetDiff(img_float, self.back_avg, self.thresh_diff_pix) if self.last_img!=[]: diff_last=GetDiff(img_float, self.last_img, self.thresh_diff_pix) self.last_img=img_float diff = diff_avg mask = np.zeros(diff.shape, np.uint8) mask[diff.shape[0] // 5:diff.shape[0] // 5 * 4, :] = diff[diff.shape[0] // 5:diff.shape[0] // 5 * 4, :] _, labels, stats, centroids = cv2.connectedComponentsWithStats(mask) # blobs_doh = blob_doh(diff, max_sigma=30, threshold=.01) blobs = [] for i, blob in enumerate(stats): if blob[-1] <= 10 or blob[-1] > img.shape[0] * img.shape[1] / 10: continue cpt = centroids[i].tolist() r = sqrt((cpt[0] - blob[0]) * (cpt[0] - blob[0]) + (cpt[1] - blob[1]) * (cpt[1] - blob[1])) cpt.append(r) blobs.append([cpt[1], cpt[0], cpt[2]]) self.fblobs[fid] = blobs # for blob in blobs_doh: # y, x, r = blob # if r <= 5: # continue # blobs.append(blob.tolist()) # self.fblobs[fid] = blobs is_drop = False start = time() if len(blobs) != 0 and fid - 1 in self.fblobs: seeds = [] for blob in blobs: for lblob in self.fblobs[fid - 1]: seed = [(int(blob[1]), int(blob[0])), (int(lblob[1]), int(lblob[0]))] if seed[0][1] > seed[1][1] and abs(seed[0][0] - seed[1][0]) < img.shape[1] // 10 and \ (seed[0][1] - seed[1][1]) < img.shape[0] // 10: seeds.append(seed) params = (fid, self.fblobs, seeds, img.shape) find_lines(params) # if len(seeds) != 0: # params = [] # for i in range(0, len(seeds), 10): # nseeds = seeds[i:i+10] # params.append((fid, self.fblobs, nseeds, img.shape)) # pool = Pool(len(params)) # ret_list = pool.map(find_lines, params) # pool.close() # pool.join() # seeds = [ro for ret in ret_list for ro in ret] for seed in seeds: if len(seed) <= 10: continue # to be add is_drop = True drop_seed = seed return diff, blobs, is_drop, drop_seed end = time() print (end - start) return diff, blobs, is_drop, [] def testdrop(): fn_v="/Users/guoxiaolu/work/Drop/2020_07_03_13_56_IMG_2005.avi" dd=DropDetect() image_back=dd.GetBackGound(fn_v,500) vc=cv2.VideoCapture(fn_v) dd.back_avg=image_back counter=0 fid = 0 basename = os.path.basename(fn_v) extnames = os.path.splitext(basename) fourcc = cv2.VideoWriter_fourcc(*'mpeg') vname = os.path.join('./', extnames[0] + '_predict.mp4') out = cv2.VideoWriter(vname, fourcc, 25, (image_back.shape[1], image_back.shape[0])) start = time() while True: res,img=vc.read() if res==False: break # temp img = cv2.resize(img, (img.shape[1] // 4, img.shape[0] // 4)) fid += 1 if fid > 100: break diff, blobs, is_drop, drop_seed = dd.GetDiff(img, fid) vis = cv2.cvtColor(diff, cv2.COLOR_GRAY2BGR) for blob in blobs: y, x, r = blob cv2.circle(vis, (int(x), int(y)), int(r), (255, 0, 0), 2) if is_drop: cv2.putText(vis,'Drop!', (50, 50),cv2.FONT_HERSHEY_COMPLEX,1,(0, 0, 255), 5) for i, seed in enumerate(drop_seed): if i >= len(drop_seed) - 2: continue cv2.line(vis, seed, drop_seed[i + 1], (0, 0, 255), 2) print (fid) cv2.imshow("img",img) cv2.imshow("diff",vis) cv2.waitKey(1) out.write(vis) print (time() - start) out.release() if __name__=="__main__": testdrop()