284 lines
12 KiB
Python
284 lines
12 KiB
Python
|
import time
|
||
|
|
from centerface import CenterFace
|
||
|
|
from skimage import transform as trans
|
||
|
|
import numpy as np
|
||
|
|
import torch
|
||
|
|
import cv2
|
||
|
|
from backbones import iresnet100, iresnet18
|
||
|
|
from create_database import findOne, load_npy,findAll
|
||
|
|
from PIL import Image, ImageDraw,ImageFont
|
||
|
|
|
||
|
|
def show():
|
||
|
|
cap = cv2.VideoCapture("test.mp4")
|
||
|
|
ret, frame = cap.read()
|
||
|
|
h, w = frame.shape[:2]
|
||
|
|
centerface = CenterFace()
|
||
|
|
size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
|
||
|
|
int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
|
||
|
|
out = cv2.VideoWriter('ccvt6.mp4', cv2.VideoWriter_fourcc('m', 'p', '4', 'v'), 30, size)
|
||
|
|
while ret:
|
||
|
|
start_time = time.time()
|
||
|
|
dets, lms = centerface(frame, h, w, threshold=0.35)
|
||
|
|
end_time = time.time()
|
||
|
|
print("findOne time: " + str(end_time - start_time))
|
||
|
|
for det in dets:
|
||
|
|
boxes, score = det[:4], det[4]
|
||
|
|
cv2.rectangle(frame, (int(boxes[0]), int(boxes[1])), (int(boxes[2]), int(boxes[3])), (2, 255, 0), 1)
|
||
|
|
for lm in lms:
|
||
|
|
for i in range(0, 5):
|
||
|
|
cv2.circle(frame, (int(lm[i * 2]), int(lm[i * 2 + 1])), 2, (0, 0, 255), -1)
|
||
|
|
cv2.imshow('out', frame)
|
||
|
|
out.write(frame)
|
||
|
|
# Press Q on keyboard to stop recording
|
||
|
|
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||
|
|
break
|
||
|
|
ret, frame = cap.read()
|
||
|
|
cap.release()
|
||
|
|
out.release()
|
||
|
|
cv2.destroyAllWindows()
|
||
|
|
|
||
|
|
def video():
|
||
|
|
model = iresnet100()
|
||
|
|
model.load_state_dict(torch.load("./model/backbone100.pth", map_location="cpu"))
|
||
|
|
model.eval()
|
||
|
|
k_v = load_npy("student.npy")
|
||
|
|
count = 0
|
||
|
|
#cap = cv2.VideoCapture("http://ivi.bupt.edu.cn/hls/cctv6hd.m3u8")
|
||
|
|
cap = cv2.VideoCapture("software.mp4")
|
||
|
|
ret, frame = cap.read()
|
||
|
|
h, w = frame.shape[:2]
|
||
|
|
size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
|
||
|
|
int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
|
||
|
|
fps = cap.get(cv2.CAP_PROP_FPS)
|
||
|
|
out = cv2.VideoWriter('ttt.mp4', cv2.VideoWriter_fourcc('m', 'p', '4', 'v'), fps, size)
|
||
|
|
centerface = CenterFace()
|
||
|
|
while ret:
|
||
|
|
start_time = time.time()
|
||
|
|
dets, lms = centerface(frame, h, w, threshold=0.35)
|
||
|
|
end_time = time.time()
|
||
|
|
print("detectOneframe time: " + str(end_time - start_time))
|
||
|
|
face_list = []
|
||
|
|
name_list = []
|
||
|
|
for i,det in enumerate(dets):
|
||
|
|
boxes, score = det[:4], det[4]
|
||
|
|
img_w = int(boxes[2] - boxes[0])
|
||
|
|
img_h = int(boxes[3] - boxes[1])
|
||
|
|
distace = int(abs(img_w - img_h) / 2)
|
||
|
|
img_w1 = int(boxes[0]) - distace
|
||
|
|
img_w2 = int(boxes[2]) + distace
|
||
|
|
# print(img_w,img_h,distace,max_hw)
|
||
|
|
if img_w <= img_h and img_w1 >= 0 and img_w2 <= frame.shape[1]:
|
||
|
|
img112 = frame[int(boxes[1]):int(boxes[3]), img_w1:img_w2, :]
|
||
|
|
img112 = cv2.resize(img112, (112, 112))
|
||
|
|
# cv2.imwrite("./img/man"+str(count)+".jpg", img112)
|
||
|
|
# count += 1
|
||
|
|
face_list.append(img112)
|
||
|
|
else:
|
||
|
|
img112 = frame[int(boxes[1]):int(boxes[3]), int(boxes[0]):int(boxes[2]), :]
|
||
|
|
img112 = cv2.resize(img112, (112, 112))
|
||
|
|
face_list.append(img112)
|
||
|
|
if len(face_list) != 0:
|
||
|
|
face_list = np.array(face_list)
|
||
|
|
face_list = face_list.transpose((0,3,1,2))
|
||
|
|
face_list = np.array(face_list, dtype=np.float32)
|
||
|
|
face_list -= 127.5
|
||
|
|
face_list /= 127.5
|
||
|
|
print(face_list.shape)
|
||
|
|
face_list = torch.from_numpy(face_list)
|
||
|
|
start_time = time.time()
|
||
|
|
|
||
|
|
for face in face_list:
|
||
|
|
face = face[np.newaxis, :, :, :]
|
||
|
|
|
||
|
|
name_list.append(findOne(face,model,k_v))
|
||
|
|
end_time = time.time()
|
||
|
|
print("findOneframe time: "+str(end_time-start_time))
|
||
|
|
img_PIL = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
|
||
|
|
draw = ImageDraw.Draw(img_PIL)
|
||
|
|
font = ImageFont.truetype("font.ttf",12)
|
||
|
|
for i,det in enumerate(dets):
|
||
|
|
boxes, score = det[:4], det[4]
|
||
|
|
# cv2.rectangle(frame, (int(boxes[0]), int(boxes[1])), (int(boxes[2]), int(boxes[3])), (2, 255, 0), 1)
|
||
|
|
# cv2.putText(frame, name_list[i], (int(boxes[0]), int(boxes[1])), cv2.FONT_HERSHEY_COMPLEX, 0.4,
|
||
|
|
# (0, 225, 255), 1)
|
||
|
|
name = name_list[i][:3]
|
||
|
|
if not isinstance(name, np.unicode):
|
||
|
|
name = name.decode('utf8')
|
||
|
|
draw.text((int(boxes[0]), int(boxes[1])),name,fill=(0, 225, 255),font=font)
|
||
|
|
draw.rectangle((int(boxes[0]), int(boxes[1]),int(boxes[2]), int(boxes[3])),outline="green",width=1)
|
||
|
|
frame = cv2.cvtColor(np.asarray(img_PIL),cv2.COLOR_RGB2BGR)
|
||
|
|
cv2.imshow('out', frame)
|
||
|
|
out.write(frame)
|
||
|
|
# Press Q on keyboard to stop recording
|
||
|
|
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||
|
|
break
|
||
|
|
ret, frame = cap.read()
|
||
|
|
cap.release()
|
||
|
|
out.release()
|
||
|
|
cv2.destroyAllWindows()
|
||
|
|
def video_GPU():
|
||
|
|
model = iresnet100()
|
||
|
|
model.load_state_dict(torch.load("./model/backbone100.pth", map_location="cpu"))
|
||
|
|
model.eval()
|
||
|
|
k_v = load_npy("student.npy")
|
||
|
|
count = 0
|
||
|
|
#cap = cv2.VideoCapture("http://ivi.bupt.edu.cn/hls/cctv6hd.m3u8")
|
||
|
|
cap = cv2.VideoCapture("software.mp4")
|
||
|
|
ret, frame = cap.read()
|
||
|
|
h, w = frame.shape[:2]
|
||
|
|
size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
|
||
|
|
int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
|
||
|
|
fps = cap.get(cv2.CAP_PROP_FPS)
|
||
|
|
out = cv2.VideoWriter('ttt.mp4', cv2.VideoWriter_fourcc('m', 'p', '4', 'v'), fps, size)
|
||
|
|
centerface = CenterFace()
|
||
|
|
while ret:
|
||
|
|
start_time = time.time()
|
||
|
|
dets, lms = centerface(frame, h, w, threshold=0.35)
|
||
|
|
end_time = time.time()
|
||
|
|
print("detectOneframe time: " + str(end_time - start_time))
|
||
|
|
face_list = []
|
||
|
|
name_list = []
|
||
|
|
for i,det in enumerate(dets):
|
||
|
|
boxes, score = det[:4], det[4]
|
||
|
|
img_w = int(boxes[2] - boxes[0])
|
||
|
|
img_h = int(boxes[3] - boxes[1])
|
||
|
|
distace = int(abs(img_w - img_h) / 2)
|
||
|
|
img_w1 = int(boxes[0]) - distace
|
||
|
|
img_w2 = int(boxes[2]) + distace
|
||
|
|
# print(img_w,img_h,distace,max_hw)
|
||
|
|
if img_w <= img_h and img_w1 >= 0 and img_w2 <= frame.shape[1]:
|
||
|
|
img112 = frame[int(boxes[1]):int(boxes[3]), img_w1:img_w2, :]
|
||
|
|
img112 = cv2.resize(img112, (112, 112))
|
||
|
|
# cv2.imwrite("./img/man"+str(count)+".jpg", img112)
|
||
|
|
# count += 1
|
||
|
|
face_list.append(img112)
|
||
|
|
else:
|
||
|
|
img112 = frame[int(boxes[1]):int(boxes[3]), int(boxes[0]):int(boxes[2]), :]
|
||
|
|
img112 = cv2.resize(img112, (112, 112))
|
||
|
|
face_list.append(img112)
|
||
|
|
if len(face_list) != 0:
|
||
|
|
face_list = np.array(face_list)
|
||
|
|
face_list = face_list.transpose((0,3,1,2))
|
||
|
|
face_list = np.array(face_list, dtype=np.float32)
|
||
|
|
face_list -= 127.5
|
||
|
|
face_list /= 127.5
|
||
|
|
print(face_list.shape)
|
||
|
|
face_list = torch.from_numpy(face_list)
|
||
|
|
start_time = time.time()
|
||
|
|
name_list = findAll(face_list, model, k_v)
|
||
|
|
# for face in face_list:
|
||
|
|
# face = face[np.newaxis, :, :, :]
|
||
|
|
#
|
||
|
|
# name_list.append(findOne(face,model,k_v))
|
||
|
|
end_time = time.time()
|
||
|
|
print("findOneframe time: "+str(end_time-start_time))
|
||
|
|
img_PIL = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
|
||
|
|
draw = ImageDraw.Draw(img_PIL)
|
||
|
|
font = ImageFont.truetype("font.ttf",18)
|
||
|
|
for i,det in enumerate(dets):
|
||
|
|
boxes, score = det[:4], det[4]
|
||
|
|
# cv2.rectangle(frame, (int(boxes[0]), int(boxes[1])), (int(boxes[2]), int(boxes[3])), (2, 255, 0), 1)
|
||
|
|
# cv2.putText(frame, name_list[i], (int(boxes[0]), int(boxes[1])), cv2.FONT_HERSHEY_COMPLEX, 0.4,
|
||
|
|
# (0, 225, 255), 1)
|
||
|
|
name = name_list[i][:3]
|
||
|
|
if not isinstance(name, np.unicode):
|
||
|
|
name = name.decode('utf8')
|
||
|
|
draw.text((int(boxes[0]), int(boxes[1])),name,fill=(255, 0, 0),font=font)
|
||
|
|
draw.rectangle((int(boxes[0]), int(boxes[1]),int(boxes[2]), int(boxes[3])),outline="green",width=2)
|
||
|
|
frame = cv2.cvtColor(np.asarray(img_PIL),cv2.COLOR_RGB2BGR)
|
||
|
|
cv2.imshow('out', frame)
|
||
|
|
out.write(frame)
|
||
|
|
# Press Q on keyboard to stop recording
|
||
|
|
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||
|
|
break
|
||
|
|
ret, frame = cap.read()
|
||
|
|
cap.release()
|
||
|
|
out.release()
|
||
|
|
cv2.destroyAllWindows()
|
||
|
|
|
||
|
|
def video_GPU_retinaface():
|
||
|
|
model = iresnet100()
|
||
|
|
model.load_state_dict(torch.load("./model/backbone100.pth", map_location="cpu"))
|
||
|
|
model.eval()
|
||
|
|
k_v = load_npy("student.npy")
|
||
|
|
count = 0
|
||
|
|
#cap = cv2.VideoCapture("http://ivi.bupt.edu.cn/hls/cctv6hd.m3u8")
|
||
|
|
cap = cv2.VideoCapture("software.mp4")
|
||
|
|
ret, frame = cap.read()
|
||
|
|
h, w = frame.shape[:2]
|
||
|
|
size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
|
||
|
|
int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
|
||
|
|
fps = cap.get(cv2.CAP_PROP_FPS)
|
||
|
|
out = cv2.VideoWriter('ttt.mp4', cv2.VideoWriter_fourcc('m', 'p', '4', 'v'), fps, size)
|
||
|
|
centerface = CenterFace()
|
||
|
|
while ret:
|
||
|
|
start_time = time.time()
|
||
|
|
dets, lms = centerface(frame, h, w, threshold=0.35)
|
||
|
|
end_time = time.time()
|
||
|
|
print("detectOneframe time: " + str(end_time - start_time))
|
||
|
|
face_list = []
|
||
|
|
name_list = []
|
||
|
|
print(dets.shape)
|
||
|
|
for i,det in enumerate(dets):
|
||
|
|
boxes, score = det[:4], det[4]
|
||
|
|
img_w = int(boxes[2] - boxes[0])
|
||
|
|
img_h = int(boxes[3] - boxes[1])
|
||
|
|
distace = int(abs(img_w - img_h) / 2)
|
||
|
|
img_w1 = int(boxes[0]) - distace
|
||
|
|
img_w2 = int(boxes[2]) + distace
|
||
|
|
# print(img_w,img_h,distace,max_hw)
|
||
|
|
if img_w <= img_h and img_w1 >= 0 and img_w2 <= frame.shape[1]:
|
||
|
|
img112 = frame[int(boxes[1]):int(boxes[3]), img_w1:img_w2, :]
|
||
|
|
img112 = cv2.resize(img112, (112, 112))
|
||
|
|
# cv2.imwrite("./img/man"+str(count)+".jpg", img112)
|
||
|
|
# count += 1
|
||
|
|
face_list.append(img112)
|
||
|
|
else:
|
||
|
|
img112 = frame[int(boxes[1]):int(boxes[3]), int(boxes[0]):int(boxes[2]), :]
|
||
|
|
img112 = cv2.resize(img112, (112, 112))
|
||
|
|
face_list.append(img112)
|
||
|
|
if len(face_list) != 0:
|
||
|
|
face_list = np.array(face_list)
|
||
|
|
face_list = face_list.transpose((0,3,1,2))
|
||
|
|
face_list = np.array(face_list, dtype=np.float32)
|
||
|
|
face_list -= 127.5
|
||
|
|
face_list /= 127.5
|
||
|
|
print(face_list.shape)
|
||
|
|
face_list = torch.from_numpy(face_list)
|
||
|
|
start_time = time.time()
|
||
|
|
name_list = findAll(face_list, model, k_v)
|
||
|
|
# for face in face_list:
|
||
|
|
# face = face[np.newaxis, :, :, :]
|
||
|
|
#
|
||
|
|
# name_list.append(findOne(face,model,k_v))
|
||
|
|
end_time = time.time()
|
||
|
|
print("findOneframe time: "+str(end_time-start_time))
|
||
|
|
img_PIL = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
|
||
|
|
draw = ImageDraw.Draw(img_PIL)
|
||
|
|
font = ImageFont.truetype("font.ttf",18)
|
||
|
|
for i,det in enumerate(dets):
|
||
|
|
boxes, score = det[:4], det[4]
|
||
|
|
# cv2.rectangle(frame, (int(boxes[0]), int(boxes[1])), (int(boxes[2]), int(boxes[3])), (2, 255, 0), 1)
|
||
|
|
# cv2.putText(frame, name_list[i], (int(boxes[0]), int(boxes[1])), cv2.FONT_HERSHEY_COMPLEX, 0.4,
|
||
|
|
# (0, 225, 255), 1)
|
||
|
|
name = name_list[i][:3]
|
||
|
|
if not isinstance(name, np.unicode):
|
||
|
|
name = name.decode('utf8')
|
||
|
|
draw.text((int(boxes[0]), int(boxes[1])),name,fill=(255, 0, 0),font=font)
|
||
|
|
draw.rectangle((int(boxes[0]), int(boxes[1]),int(boxes[2]), int(boxes[3])),outline="green",width=2)
|
||
|
|
frame = cv2.cvtColor(np.asarray(img_PIL),cv2.COLOR_RGB2BGR)
|
||
|
|
cv2.imshow('out', frame)
|
||
|
|
out.write(frame)
|
||
|
|
# Press Q on keyboard to stop recording
|
||
|
|
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||
|
|
break
|
||
|
|
ret, frame = cap.read()
|
||
|
|
cap.release()
|
||
|
|
out.release()
|
||
|
|
cv2.destroyAllWindows()
|
||
|
|
|
||
|
|
|
||
|
|
video_GPU_retinaface()
|
||
|
|
#video_GPU()
|
||
|
|
#show()
|