def frame2emocrop(frame, threshold=0.9, qps=2, input_size=(1024, 1024), output_size=(256, 256), save_dir='.', fmt='.png'):
sleep(1 / qps)
img_base64 = frame2base64(frame)
img = cv2.resize(img, input_size)
res = client.detect(img_base64, img_type, options)
if res['error_code'] != 0:
return None
for face in res['result']['face_list']:
if face['emotion']['probability'] < threshold:
continue
emotion = face['emotion']['type']
face_token = face['face_token']
loc = face['location']
top = int(loc['top'])
bottom = int(loc['top'] + loc['height'])
left = int(loc['left'])
right = int(loc['left'] + loc['width'])
rotation = loc['rotation']
crop = frame[top:bottom, left:right]
crop = cv2.resize(crop, output_size)
ensure_dir(f'{save_dir}/{emotion}')
cv2.imwrite(f'{save_dir}/{emotion}/{face_token}{fmt}', crop)
return res
def imcompose(imgs, save_path='compose.png', width=256, height=256):
assert len(imgs) >= 1, "The imgs can't be none!"
row, col = len(imgs), len(imgs[0])
target = Image.new('RGB', (col * width, row * height))
for i, img_row in enumerate(imgs):
for j, img in enumerate(img_row):
tmp = Image.open(img).resize((width, height), Image.ANTIALIAS)
target.paste(tmp, (j * width, i * height))
ensure_dir(save_path)
return target.save(save_path)
def fontset(ttf, chars=None, img_size=[256,256], font_size=240, background="black", bg_value=(255,255,255), start_pos=(8,8), mode='scc', save_dir=''):
assert chars != None, 'The chars can not be None.'
font = ImageFont.truetype(ttf, font_size)
font_dir = ttf.rstrip('.ttf') if save_dir == '' else save_dir
ensure_dir(font_dir)
for c in chars:
try:
im = Image.new("RGB", img_size, background)
im_draw = ImageDraw.Draw(im)
im_draw.text(start_pos, c, bg_value, font)
im.save(f"{font_dir}/{c}.png")
except:
print(f'Process {c} error.')
return False
return True
def gif2img(infile, save_dir=None):
if not save_dir:
save_dir = infile.rsplit('.', 1)[0]
try:
im = Image.open(infile)
except IOError:
print("Cant load", infile)
ensure_dir(save_dir)
cnt = 0
palette = im.getpalette()
try:
while True:
if not im.getpalette():
im.putpalette(palette)
new_im = Image.new("RGBA", im.size)
new_im.paste(im)
new_im.save(f'{save_dir}/{cnt}.png')
cnt += 1
im.seek(im.tell() + 1)
except EOFError:
print(f"gif to {cnt} imgs done")
return cnt
def im2emocrop(img_path, threshold=0.9, qps=2, input_size=(256, 256), output_size=(256, 256), save_dir='.', align=False, fmt='.png'):
sleep(1 / qps)
try:
img = cv2.imread(img_path)
if img.shape != input_size:
img = cv2.resize(img, input_size)
except Exception as e:
print(f'{img_path}:', e)
return None
# 方式1
# img_base64 = im2base64(img_path)
# 方式2
img_base64 = frame2base64(img)
res = client.detect(img_base64, img_type, options)
if res['error_code'] != 0:
return res
for face in res['result']['face_list']:
if face['emotion']['probability'] < threshold:
continue
emotion = face['emotion']['type']
face_token = face['face_token']
loc = face['location']
if align:
top = int(loc['top'])
bottom = int(loc['top'] + loc['height'])
left = int(loc['left'])
right = int(loc['left'] + loc['width'])
rotation = loc['rotation']
crop = img[top:bottom, left:right]
else:
crop = img
if crop.shape != output_size:
crop = cv2.resize(crop, output_size)
ensure_dir(f'{save_dir}/{emotion}')
cv2.imwrite(f'{save_dir}/{emotion}/{face_token}{fmt}', crop)
return res
def imresize(img_path, save_dir='.', size=(256, 256)):
name = img_path.rsplit('/', 1)[-1]
im = Image.open(img_path).resize(size, Image.ANTIALIAS)
ensure_dir(save_dir)
im.save(f'{save_dir}/{name}')
def align_faces(raw_dir, align_dir, min_input_size=(256,256), output_size=1024, transform_size=1024, x_scale=1, y_scale=1, em_scale=0.1, alpha=False):
ensure_dir(align_dir)
for img_name in os.listdir(raw_dir):
print(f'Aligning {img_name} ...')
raw_img_path = os.path.join(raw_dir, img_name)
try:
img = cv2.imread(raw_img_path)
if img.shape[0] < min_input_size[0] or img.shape[1] < min_input_size[1]:
continue
except:
print(f'Read {img_name} error.')
continue
fn = face_img_name = '%s_%02d.png' % (os.path.splitext(img_name)[0], 1)
if os.path.isfile(fn):
continue
try:
print('Getting landmarks...')
for i, face_landmarks in enumerate(landmarks_detector.get_landmarks(raw_img_path), start=1):
try:
print('Starting face alignment...')
face_img_name = '%s_%02d.png' % (os.path.splitext(img_name)[0], i)
aligned_face_path = os.path.join(align_dir, face_img_name)
face_align(raw_img_path, aligned_face_path, face_landmarks,
output_size=output_size, transform_size=transform_size,
x_scale=x_scale, y_scale=y_scale, em_scale=em_scale, alpha=alpha)
print('Wrote result %s' % aligned_face_path)
except:
print("Exception in face alignment!")
except:
print("Exception in landmark detection!")
def video2img(infile, save_dir=None):
if not save_dir:
save_dir = infile.rsplit('.', 1)[0]
try:
vc = cv2.VideoCapture(infile)
rval = vc.isOpened()
except:
print("Cant load", infile)
return
if not os.path.exists(save_dir):
os.mkdir(save_dir)
cnt = 0
rval, frame = vc.read()
while rval:
cv2.imwrite(f'{save_dir}/{cnt}.jpg', frame)
cnt += 1
rval, frame = vc.read()
print(f"video to {cnt} imgs done")
def gif2img(infile, save_dir=None):
if not save_dir:
save_dir = infile.rsplit('.', 1)[0]
try:
im = Image.open(infile)
except IOError:
print("Cant load", infile)
ensure_dir(save_dir)
cnt = 0
palette = im.getpalette()
try:
while True:
if not im.getpalette():
im.putpalette(palette)
new_im = Image.new("RGBA", im.size)
new_im.paste(im)
new_im.save(f'{save_dir}/{cnt}.png')
cnt += 1
im.seek(im.tell() + 1)
except EOFError:
print(f"gif to {cnt} imgs done")
return cnt
def fontset(ttf, chars=None, img_size=[256,256], font_size=240, background="black", bg_value=(255,255,255), start_pos=(8,8), mode='scc', save_dir=''):
assert chars != None, 'The chars can not be None.'
font = ImageFont.truetype(ttf, font_size)
font_dir = ttf.rstrip('.ttf') if save_dir == '' else save_dir
ensure_dir(font_dir)
for c in chars:
try:
im = Image.new("RGB", img_size, background)
im_draw = ImageDraw.Draw(im)
im_draw.text(start_pos, c, bg_value, font)
im.save(f"{font_dir}/{c}.png")
except:
print(f'Process {c} error.')
return False
return True
