-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathavnet_face_detection.py
129 lines (102 loc) · 3.6 KB
/
avnet_face_detection.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
'''
Copyright 2020 Avnet Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
'''
# USAGE
# python avnet_face_detection.py [--input 0] [--detthreshold 0.55] [--nmsthreshold 0.35]
import numpy as np
import argparse
import imutils
import time
import cv2
import os, errno
from imutils.video import FPS
from vitis_ai_vart.facedetect import FaceDetect
import runner
import xir.graph
import pathlib
import xir.subgraph
def get_subgraph (g):
sub = []
root = g.get_root_subgraph()
sub = [ s for s in root.children
if s.metadata.get_attr_str ("device") == "DPU"]
return sub
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--input", required=False,
help = "input camera identifier (default = 0)")
ap.add_argument("-d", "--detthreshold", required=False,
help = "face detector softmax threshold (default = 0.55)")
ap.add_argument("-n", "--nmsthreshold", required=False,
help = "face detector NMS threshold (default = 0.35)")
args = vars(ap.parse_args())
if not args.get("input",False):
inputId = 0
else:
inputId = int(args["input"])
print('[INFO] input camera identifier = ',inputId)
if not args.get("detthreshold",False):
detThreshold = 0.55
else:
detThreshold = float(args["detthreshold"])
print('[INFO] face detector - softmax threshold = ',detThreshold)
if not args.get("nmsthreshold",False):
nmsThreshold = 0.35
else:
nmsThreshold = float(args["nmsthreshold"])
print('[INFO] face detector - NMS threshold = ',nmsThreshold)
# Initialize Vitis-AI/DPU based face detector
densebox_elf = "/usr/share/vitis_ai_library/models/densebox_640_360/densebox_640_360.elf"
densebox_graph = xir.graph.Graph.deserialize(pathlib.Path(densebox_elf))
densebox_subgraphs = get_subgraph(densebox_graph)
assert len(densebox_subgraphs) == 1 # only one DPU kernel
densebox_dpu = runner.Runner(densebox_subgraphs[0],"run")
dpu_face_detector = FaceDetect(densebox_dpu,detThreshold,nmsThreshold)
dpu_face_detector.start()
# Initialize the camera input
print("[INFO] starting camera input ...")
cam = cv2.VideoCapture(inputId)
cam.set(cv2.CAP_PROP_FRAME_WIDTH,640)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,480)
if not (cam.isOpened()):
print("[ERROR] Failed to open camera ", inputId )
exit()
# start the FPS counter
fps = FPS().start()
# loop over the frames from the video stream
while True:
# Capture image from camera
ret,frame = cam.read()
# Vitis-AI/DPU based face detector
faces = dpu_face_detector.process(frame)
# loop over the faces
for i,(left,top,right,bottom) in enumerate(faces):
# draw a bounding box surrounding the object so we can
# visualize it
cv2.rectangle( frame, (left,top), (right,bottom), (0,255,0), 2)
# Display the processed image
cv2.imshow("Face Detection", frame)
key = cv2.waitKey(1) & 0xFF
# Update the FPS counter
fps.update()
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
# Stop the timer and display FPS information
fps.stop()
print("[INFO] elapsed time: {:.2f}".format(fps.elapsed()))
print("[INFO] elapsed FPS: {:.2f}".format(fps.fps()))
# Stop the face detector
dpu_face_detector.stop()
del densebox_dpu
# Cleanup
cv2.destroyAllWindows()