refactor face detection code

This commit is contained in:
Feier Zhang 2020-10-28 23:56:14 -04:00
parent 081fa68162
commit 7284e5f0d1
23 changed files with 67 additions and 40 deletions

View file

@ -1,62 +1,89 @@
import sys
import os
import cv2
import numpy as np
import sys,os,numpy
from glob import glob
from skimage import io
#read test photo
pwd = sys.path[0]
img = cv2.imread(pwd + "/Facial_test_images/6.jpg")
grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
def face_detector_haarcascade(image):
resize_fx = 1
resize_fy = 1
grey = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
grey = cv2.resize(grey, dsize=None, fx=resize_fx, fy=resize_fy, interpolation = cv2.INTER_AREA)
resize_fx = 1
resize_fy = 1
grey = cv2.resize(grey, dsize=None, fx=resize_fx, fy=resize_fy, interpolation = cv2.INTER_AREA)
pwd = sys.path[0]
classfier = cv2.CascadeClassifier(pwd + "/Facial_models/haarcascade_frontalface_alt2.xml")
faceRects = classfier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=1, minSize=(16, 16))
if len(faceRects) > 0:
for faceRect in faceRects:
x, y, w, h = faceRect
x = int(x/resize_fx)
y = int(y/resize_fy)
w = int(w/resize_fx)
h = int(h/resize_fy)
cv2.rectangle(image, (x - 10, y - 10), (x + w + 10, y + h + 10), (0, 255, 0), 5)
return image
classfier = cv2.CascadeClassifier(pwd + "/Facial_models/haarcascade_frontalface_alt2.xml")
def face_detector_ssd(image):
faceRects = classfier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=1, minSize=(16, 16))
pwd = sys.path[0]
net = cv2.dnn.readNetFromCaffe(pwd+"/Facial_models/deploy.prototxt", pwd+"/Facial_models/res10_300x300_ssd_iter_140000_fp16.caffemodel")
color = (0, 255, 0)
if len(faceRects) > 0:
for faceRect in faceRects:
x, y, w, h = faceRect
x = int(x/resize_fx)
y = int(y/resize_fy)
w = int(w/resize_fx)
h = int(h/resize_fy)
cv2.rectangle(img, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 5)
resize = (800, 800)
confidence_thres = 0.65
cv2.imwrite(pwd + "/Facial_test_images/output-a.jpg",img)
cv2.imshow("face_image_a",img)
blob = cv2.dnn.blobFromImage(cv2.resize(image, dsize=resize), 1.0, resize, (104.0, 177.0, 123.0))
# blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))
net.setInput(blob)
detections = net.forward()
h,w,c=image.shape
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > confidence_thres:
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
text = "{:.2f}%".format(confidence * 100)
y = startY - 10 if startY - 10 > 10 else startY + 10
cv2.rectangle(image, (startX, startY), (endX, endY),(0, 255,0), 5)
cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 1.00, (0, 255, 0), 3)
return image
image = cv2.imread(pwd + "/Facial_test_images/6.jpg")
if __name__=="__main__":
net = cv2.dnn.readNetFromCaffe(pwd+"/Facial_models/deploy.prototxt", pwd+"/Facial_models/res10_300x300_ssd_iter_140000_fp16.caffemodel")
image_name = "8.jpg"
split_name = image_name.split(".")
blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))
image_read_path = sys.path[0]+"/Facial_test_images/"+image_name
image_save_path = sys.path[0]+"/Facial_test_images/output/"+split_name[0]+"_result."+split_name[1]
image = cv2.imread(image_read_path)
image = face_detector_ssd(image)
#image = face_detector_haarcascade(image)
print(image_save_path)
cv2.imwrite(image_save_path, image)
cv2.imshow("result", image)
cv2.waitKey()
cv2.destroyAllWindows()
net.setInput(blob)
detections = net.forward()
h,w,c=image.shape
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > 0.65:
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
text = "{:.2f}%".format(confidence * 100)
y = startY - 10 if startY - 10 > 10 else startY + 10
cv2.rectangle(image, (startX, startY), (endX, endY),(0, 255,0), 5)
cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 1.00, (0, 255, 0), 3)
cv2.imwrite(pwd + "/Facial_test_images/output-b.jpg", image)
cv2.imshow("face_image_b",image)
cv2.waitKey(0)

Binary file not shown.

Before

Width:  |  Height:  |  Size: 81 KiB

After

Width:  |  Height:  |  Size: 80 KiB

BIN
Facial_test_images/8.jpg Normal file

Binary file not shown.

After

Width:  |  Height:  |  Size: 106 KiB

BIN
Facial_test_images/9.jpg Normal file

Binary file not shown.

After

Width:  |  Height:  |  Size: 90 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 236 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 240 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 267 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 145 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 292 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 329 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 240 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 159 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 162 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 196 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 203 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 170 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 178 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 270 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 129 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 179 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 273 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 331 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 235 KiB