def detect_face(record_id, filepath):
"""
调用face++ API检测人脸并写入数据库
:param record_id: (int) 数据库记录
:param file_path: (string) 图像路径
:return: (int) 是否检测到人脸（默认选第一个）
"""
files = {'image_file': (os.path.basename(filepath),
open(filepath, 'rb'),
mimetypes.guess_type(filepath)[0]),}
response = requests.post(url, files=files)
info = response.json()
FemaleFace.update(record_id, info=json.dumps(info))
faces = info.get('faces', [])
print faces
if not faces:
return 0
landmark = faces[0].get('landmark',[])
print landmark
if not landmark:
return 0
FemaleFace.update(record_id, landmark=json.dumps(landmark))
return 1
def detect_face(record_id, file_path):
"""
调用face++ API检测人脸并写入数据库
:param record_id: (int) 数据库记录
:param file_path: (string) 图像路径
:return: (int) 是否检测到人脸（默认选第一个）
"""
upload_url = '{}/detect?api_key={}&api_secret={}&return_landmark=1'.format(
BASE_URL, API_KEY, API_SECRET)
files = {
'image_file': (os.path.basename(file_path), open(file_path, 'rb'),
mimetypes.guess_type(file_path)[0]),
}
response = requests.post(upload_url, files=files)
info = response.json()
FemaleFace.update(record_id, info=json.dumps(info))
faces = info.get('faces', [])
if not faces:
return 0
#print faces
#face_id = faces[0].get('face_id', '')
#landmark_url = '{}/landmark?api_key={}&api_secret={}&face_id={}&type=83p'.format(
# BASE_URL, API_KEY, API_SECRET, face_id
#)
#response = requests.get(landmark_url)
#landmarks = response.json().get('result', [])
landmark = faces[0].get('landmark', [])
if not landmark:
return 0
FemaleFace.update(record_id, landmark=json.dumps(landmark))
return 1
def get_face_record(offset=0):
"""读取头像信息"""
global face_record
filename = get_filename(offset)
face_record = FemaleFace.get(filename)
if not face_record:
face_record = FemaleFace.add(filename, label=-1)
def detect_face(record_id, file_path):
"""
调用face++ API检测人脸并写入数据库
:param record_id: (int) 数据库记录
:param file_path: (string) 图像路径
:return: (int) 是否检测到人脸（默认选第一个）
"""
upload_url = '{}/detection/detect?api_key={}&api_secret={}&attribute=pose'.format(
BASE_URL, API_KEY, API_SECRET
)
files = {'img': (os.path.basename(file_path),
open(file_path, 'rb'),
mimetypes.guess_type(file_path)[0]), }
response = requests.post(upload_url, files=files)
info = response.json()
FemaleFace.update(record_id, info=json.dumps(info))
faces = info.get('face', [])
if not faces:
return 0
face_id = faces[0].get('face_id', '')
landmark_url = '{}/detection/landmark?api_key={}&api_secret={}&face_id={}&type=83p'.format(
BASE_URL, API_KEY, API_SECRET, face_id
)
response = requests.get(landmark_url)
landmarks = response.json().get('result', [])
if not landmarks:
return 0
landmark = landmarks[0].get('landmark')
if not landmark:
return 0
FemaleFace.update(record_id, landmark=json.dumps(landmark))
return 1
def readImages(fileList) :
imagesArray, pointsArray = [], []
#List all files in the directory and read points from text files one by one
for filePath in fileList:
if filePath.endswith(".jpg"):
# Read image found.
img = cv2.imread(filePath)
# Convert to floating point
img = np.float32(img)/255.0
# Add to array of images
imagesArray.append(img)
filename = os.path.basename(filePath)
landmark = json.loads(FemaleFace.get(filename).landmark)
pointsArray.append(readPoints(landmark))
return imagesArray, pointsArray
def readImages(fileList) :
imagesArray, pointsArray = [], []
#List all files in the directory and read points from text files one by one
for filePath in fileList:
if filePath.endswith(".jpg"):
# Read image found.
img = cv2.imread(filePath)
# Convert to floating point
img = np.float32(img)/255.0
# Add to array of images
imagesArray.append(img)
filename = os.path.basename(filePath)
landmark = json.loads(FemaleFace.get(filename).landmark)
pointsArray.append(readPoints(landmark))
return imagesArray, pointsArray
# Copy triangular region of the rectangular patch to the output image
img2[r2[1]:r2[1]+r2[3], r2[0]:r2[0]+r2[2]] = img2[r2[1]:r2[1]+r2[3], r2[0]:r2[0]+r2[2]] * ( (1.0, 1.0, 1.0) - mask )
img2[r2[1]:r2[1]+r2[3], r2[0]:r2[0]+r2[2]] = img2[r2[1]:r2[1]+r2[3], r2[0]:r2[0]+r2[2]] + img2Rect
if __name__ == '__main__' :
# Dimensions of output image
w = 600
h = 600
# 0丑 1一般 2漂亮
fileList = FemaleFace.get_file_by_label(2)
fileList = [u'../data/{}'.format(x) for x in fileList]
# Read all images
images, allPoints = readImages(fileList)
# Eye corners
eyecornerDst = [ (np.int(0.35 * w ), np.int(h / 2)), (np.int(0.65 * w ), np.int(h / 2)) ]
imagesNorm = []
pointsNorm = []
# Add boundary points for delaunay triangulation
boundaryPts = np.array([(0,0), (w/2,0), (w-1,0), (w-1,h/2), ( w-1, h-1 ), ( w/2, h-1 ), (0, h-1), (0,h/2) ])
# Initialize location of average points to 0s
pointsAvg = np.array([(0,0)]* ( len(allPoints[0]) + len(boundaryPts) ), np.float32())
def set_face_label():
"""设置头像标签"""
print face_record.id,face_label.get()
FemaleFace.update(face_record.id, label=face_label.get())
handle_next()
# Copy triangular region of the rectangular patch to the output image
img2[r2[1]:r2[1]+r2[3], r2[0]:r2[0]+r2[2]] = img2[r2[1]:r2[1]+r2[3], r2[0]:r2[0]+r2[2]] * ( (1.0, 1.0, 1.0) - mask )
img2[r2[1]:r2[1]+r2[3], r2[0]:r2[0]+r2[2]] = img2[r2[1]:r2[1]+r2[3], r2[0]:r2[0]+r2[2]] + img2Rect
if __name__ == '__main__' :
# Dimensions of output image
w = 500
h = 500
# 0丑 1一般 2漂亮
fileList = FemaleFace.get_file_by_label(2)
fileList = [u'/Users/ruoyuliu/Downloads/aaa/{}'.format(x) for x in fileList]
# Read all images
images, allPoints = readImages(fileList)
# Eye corners
eyecornerDst = [ (np.int(0.3 * w ), np.int(h / 3)), (np.int(0.7 * w ), np.int(h / 3)) ]
imagesNorm = []
pointsNorm = []
# Add boundary points for delaunay triangulation
boundaryPts = np.array([(0,0), (w/2,0), (w-1,0), (w-1,h/2), ( w-1, h-1 ), ( w/2, h-1 ), (0, h-1), (0,h/2) ])
# Initialize location of average points to 0s
pointsAvg = np.array([(0,0)]* ( len(allPoints[0]) + len(boundaryPts) ), np.float32())