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louiscklaw
2025-02-01 01:19:51 +08:00
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594
task1/_lab/007-test/test_case/beach_test/cascade.xml Normal file
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544
task1/_lab/007-test/test_case/beach_test/cascade_working_example.xml Normal file
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45
task1/_lab/007-test/test_case/beach_test/test.py Normal file
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import cv2
import os,sys
# 获取 XML 文件，加载人脸检测器
faceCascade = cv2.CascadeClassifier("cascade.xml")
# remove all jpg files in iut_re folder
for f in os.listdir("iut_re"):
if f.endswith(".jpg"):
os.remove(os.path.join("iut_re", f))
image_set = []
for f in os.listdir("iut"):
if f.endswith(".jpg"):
file_name = os.path.join("iut", f)
image_set.append([cv2.imread(file_name), file_name])
for i in range(len(image_set)):
image = image_set[i][0]
file_name = image_set[i][1]
re_file_name = file_name.replace(".jpg","_re.jpg").replace('iut/', 'iut_re/')
# 色彩转换，转换为灰度图像
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# 调用函数 detectMultiScale
faces = faceCascade.detectMultiScale(gray, scaleFactor=1.15, minNeighbors=5, minSize=(5, 5))
# print(faces)
# 打印输出的测试结果
# print("found {0} face in {1}".format(len(faces), os.path.basename(file_name)))
print((re_file_name, len(faces)))
# 逐个标注人脸
for x, y, w, h in faces:
cv2.rectangle(image, (x, y), (x + w, y + w), (0, 255, 0), 2) # 矩形标注
# cv2.circle(image,(int((x+x+w)/2),int((y+y+h)/2)),int(w/2),(0,255,0),2)
# 显示结果
cv2.imshow("dect", image)
# 保存检测结果
cv2.imwrite(re_file_name, image)
# cv2.waitKey(0)
cv2.destroyAllWindows()

5
task1/_lab/007-test/test_case/beach_test/test.sh Executable file
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@@ -0,0 +1,5 @@
#!/usr/bin/env bash
set -ex
npx nodemon --ext xml --exec "python ./test.py"

5
task1/_lab/007-test/test_case/beach_test/test_w.sh Executable file
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@@ -0,0 +1,5 @@
#!/usr/bin/env bash
set -ex
python ./test.py