#-*-coding:utf-8-*- ''' DpCas-Light |||| ||||| |||| || ||||||| || || || || || || |||| || || || || || || || || || || || || || || || || ||====|| |||||| || || ||||| || || ||======|| || || || || || || || || || || |||| || |||| || || ||||||| /--------------------- Who You Want To See ---------------------/ ''' # date:2021-04-18 # Author: Eric.Lee # function: who you want to see "你想看谁" import os import cv2 import time from multiprocessing import Process from multiprocessing import Manager import numpy as np import random import time import shutil # 加载模型组件库 from face_detect.yolo_v3_face import yolo_v3_face_model from insight_face.face_verify import insight_face_model from face_multi_task.face_multi_task_component import FaceMuitiTask_Model from face_euler_angle.face_euler_angle_component import FaceAngle_Model # 加载工具库 import sys sys.path.append("./lib/wyw2s_lib/") from cores.wyw2s_fuction import get_faces_batch_attribute from utils.utils import parse_data_cfg from utils.show_videos_thread import run_show from moviepy.editor import * def main_wyw2s(video_path,cfg_file): config = parse_data_cfg(cfg_file) print("\n/---------------------- main_wyw2s config ------------------------/\n") for k_ in config.keys(): print("{} : {}".format(k_,config[k_])) print("\n/------------------------------------------------------------------------/\n") print("\n loading who you want 2 see local demo ...\n") face_detect_model = yolo_v3_face_model(conf_thres=float(config["detect_conf_thres"]),nms_thres=float(config["detect_nms_thres"]), model_arch = config["detect_model_arch"],model_path = config["detect_model_path"],yolo_anchor_scale = float(config["yolo_anchor_scale"]), img_size = float(config["detect_input_size"]), ) face_verify_model = insight_face_model(backbone_model_path =config["face_verify_backbone_path"] , facebank_path = config["facebank_path"], threshold = float(config["face_verify_threshold"])) face_multitask_model = FaceMuitiTask_Model(model_path = config["face_multitask_model_path"], model_arch = config["face_multitask_model_arch"]) face_euler_model = FaceAngle_Model(model_path = config["face_euler_model_path"]) print("\n/------------------------------------------------------------------------/\n") YouWantToSee = config["YouWantToSee"] YouWantToSee_=[name_ for name_ in YouWantToSee.split(",")] print(" YouWantToSee : {}".format(YouWantToSee_)) print("\n/------------------------------------------------------------------------/\n") p_colors = [] for i in range(len(face_verify_model.face_names)): if i == 0 : p_colors.append((100,155,100)) if i == 1 : p_colors.append((0,255,0)) elif i == 2: p_colors.append((255,0,0)) elif i == 3: p_colors.append((0,255,255)) elif i == 4: p_colors.append((0,185,255)) elif i == 5: p_colors.append((255,185,55)) else: p_colors.append((random.randint(60,255),random.randint(70,255),random.randint(130,255))) cap = cv2.VideoCapture(video_path) frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) # 时间轴 time_map = np.zeros([200,frame_count,3]).astype(np.uint8) time_map[:,:,0].fill(105) time_map[:,:,1].fill(105) time_map[:,:,2].fill(105) pts_last = None frame_idx = 0 Flag_Last,Flag_Now = False,False start_time = 0. YouWantToSee_time_list = [] while cap.isOpened(): ret,img = cap.read() if ret: frame_idx += 1 video_time = cap.get(cv2.CAP_PROP_POS_MSEC) algo_image = img.copy() faces_bbox =face_detect_model.predict(img,vis = True) # 检测手，获取手的边界框 if len(faces_bbox) > 0: faces_identify,faces_identify_bboxes,bboxes,face_map = get_faces_batch_attribute(face_multitask_model,face_euler_model,faces_bbox,algo_image,use_cuda = True,vis = True) YouHaveSeen_list = [] if len(faces_identify) > 0: results, face_dst = face_verify_model.predict(faces_identify) face_dst = list(face_dst.cpu().detach().numpy()) # print("face_dst : ",face_dst) for idx,bbox_ in enumerate(faces_identify_bboxes): cv2.putText(algo_image, "{}: {:.2f}".format(face_verify_model.face_names[results[idx] + 1],face_dst[idx]), (bbox_[0],bbox_[1]+23),cv2.FONT_HERSHEY_DUPLEX, 0.7, (255, 95,220), 5) cv2.putText(algo_image, "{}: {:.2f}".format(face_verify_model.face_names[results[idx] + 1],face_dst[idx]), (bbox_[0],bbox_[1]+23),cv2.FONT_HERSHEY_DUPLEX, 0.7, p_colors[results[idx] + 1], 2) if face_verify_model.face_names[results[idx] + 1] in YouWantToSee_: YouHaveSeen_list.append(face_verify_model.face_names[results[idx] + 1]) # 绘制时间轴 if len(YouHaveSeen_list)>0: cv2.rectangle(time_map, (frame_idx-1,0), (frame_idx,100), (0,255,0), -1) # 绘制时间轴 print(" YouHaveSeen : {}".format(YouHaveSeen_list)) Flag_Now = True else: cv2.rectangle(time_map, (frame_idx-1,100), (frame_idx,200), (255,0,0), -1) # 绘制时间轴 print(" ------ ") Flag_Now = False else: face_map = np.zeros([112*3,112*3,3]).astype(np.uint8) face_map[:,:,0].fill(205) face_map[:,:,1].fill(205) face_map[:,:,2].fill(205) print(" ------ ") Flag_Now = False cv2.rectangle(time_map, (frame_idx-1,100), (frame_idx,200), (255,0,0), -1) # 绘制时间轴 cv2.line(time_map, (frame_idx,100),(frame_idx,100), (0,80,255), 8) # 绘制时间轴 中轴线 #------------- if Flag_Now == True and Flag_Last == False: start_time = video_time elif Flag_Now == False and Flag_Last == True: YouWantToSee_time_list.append((start_time/1000.,video_time/1000.)) Flag_Last = Flag_Now # cv2.putText(algo_image, "WhoYouWant 2 See", (algo_image.shape[1]-420,45),cv2.FONT_HERSHEY_DUPLEX, 1.2, (205, 95,250), 7) cv2.putText(algo_image, "WhoYouWant 2 See", (algo_image.shape[1]-420,45),cv2.FONT_HERSHEY_DUPLEX, 1.2, (12, 255,12), 2) cv2.putText(algo_image, "DpCas -", (algo_image.shape[1]-620,45),cv2.FONT_HERSHEY_DUPLEX, 1.2, (255, 95,210), 7) cv2.putText(algo_image, "DpCas -", (algo_image.shape[1]-620,45),cv2.FONT_HERSHEY_DUPLEX, 1.2, (12, 255,12), 2) cv2.rectangle(algo_image, (algo_image.shape[1]-640,5), (algo_image.shape[1]-30,65), (0,185,255), 6) cv2.rectangle(algo_image, (algo_image.shape[1]-640,5), (algo_image.shape[1]-30,65), (255,100,100), 2) cv2.putText(algo_image, "[{}/{}]".format(frame_idx,frame_count), (5,30),cv2.FONT_HERSHEY_DUPLEX, 1.0, (255, 95,220), 5) cv2.putText(algo_image, "[{}/{}]".format(frame_idx,frame_count), (5,30),cv2.FONT_HERSHEY_DUPLEX, 1.0, (12, 255,12), 2) cv2.putText(algo_image, "[{:.2f} sec]".format(video_time/1000.), (5,70),cv2.FONT_HERSHEY_DUPLEX, 1.0, (15, 185,255), 7) cv2.putText(algo_image, "[{:.2f} sec]".format(video_time/1000.), (5,70),cv2.FONT_HERSHEY_DUPLEX, 1.0, (255, 112,112), 2) # cv2.putText(face_map, "YouWantToSee {}".format(YouWantToSee_), (5,face_map.shape[0]-3),cv2.FONT_HERSHEY_DUPLEX, 0.55, (255, 95,220), 5) cv2.putText(face_map, "YouWantToSee {}".format(YouWantToSee_), (5,face_map.shape[0]-3),cv2.FONT_HERSHEY_DUPLEX, 0.55, (12, 215,12), 1) face_map = cv2.resize(face_map,(algo_image.shape[0],algo_image.shape[0])) algo_image = np.hstack((algo_image,face_map)) # 合并显示 time_map_r = cv2.resize(time_map,(algo_image.shape[1],200)) algo_image = np.vstack((algo_image,time_map_r)) cv2.namedWindow('WhoYouWant2See', 0) cv2.imshow('WhoYouWant2See', algo_image) key_id = cv2.waitKey(1) if key_id == 27: break else: break #------------- print("\n ----->>> YouWantToSee_Time_list : \n") movie = VideoFileClip(video_path) video_s = "./clip_wyw2s/" if os.path.exists(video_s): #删除之前的文件夹 shutil.rmtree(video_s) if not os.path.exists(video_s): # 如果文件夹不存在 os.mkdir(video_s) # 生成文件夹 seg_idx = 0 for seg_ in YouWantToSee_time_list: seg_idx += 1 print(" Seg {} : {}".format(seg_idx,seg_)) print(" 开始剪切目标人物视频 第 {} 段 \n".format(seg_idx)) movie_clip = movie.subclip(seg_[0],seg_[1])# 将剪切的片段保存 movie_clip.write_videofile("{}clip_{}.mp4".format(video_s,seg_idx)) run_show(path = video_s , vis = True) cv2.destroyAllWindows()