我正在尝试检测人脸并在人脸对齐后返回一个 img 对应的地标。这是我的代码：
def getIthFrame(self, i):
img = self.data.get_data(i)
raw_img = Image.fromarray(img)
w, h = raw_img.size
if self.pos == "center":
img, landmarks = self.detectLandmarks(raw_img)
elif self.pos == "left":
img, landmarks = self.detectLandmarks(raw_img.crop(box=(0,0, w//2, h)))
elif self.pos == "right":
img, landmarks = self.detectLandmarks(raw_img.crop(box=(w//2,0, w, h)))
elif self.pos == "90": # face oriented to right
img, landmarks = self.detectLandmarks(raw_img.rotate(90)) # rotate anticlockwise 90
elif self.pos == "180": # face oriented to down
img, landmarks = self.detectLandmarks(raw_img.rotate(180))
elif self.pos == "270": # face oriented to left
img, landmarks = self.detectLandmarks(raw_img.rotate(270))
if landmarks is None: return None, None # landmark detection fail
img, landmarks = normalize(img, landmarks)
return img, landmarks
def showImgLandmarks(self, img, landmarks=None, ax=None):
"""
visualize i-th frame with landmarks
"""
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.imshow(img)
if landmarks is not None:
ax.scatter(landmarks[:,0], landmarks[...,1])
for i in range(landmarks.shape[0]):
ax.text(landmarks[i,0], landmarks[i,1], i)
plt.show()
face_detector = dlib.get_frontal_face_detector()
landmark_detector = dlib.shape_predictor('./shape_predictor_68_face_landmarks.dat')
extractor = FrameExtract(face_detector, landmark_detector)
extractor.showImgLandmarks(*extractor.getIthFrame(0))
但是，当我尝试查看数据集中的图像时，我遇到了 TypeError：dtype 对象的图像数据无法转换为浮点数。我在线收到以下错误消息：
extractor.showImgLandmarks(*extractor.getIthFrame(0))
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-9-3429da19673c> in <module>
----> 1 extractor.showImgLandmarks(*extractor.getIthFrame(0))
<ipython-input-3-6cc47ac83d27> in showImgLandmarks(self, img, landmarks, ax)
62 fig = plt.figure()
63 ax = fig.add_subplot(1,1,1)
---> 64 ax.imshow(img)
65 if landmarks is not None:
66 ax.scatter(landmarks[:,0], landmarks[...,1])
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\__init__.py in inner(ax, data, *args, **kwargs)
1563 def inner(ax, *args, data=None, **kwargs):
1564 if data is None:
-> 1565 return func(ax, *map(sanitize_sequence, args), **kwargs)
1566
1567 bound = new_sig.bind(ax, *args, **kwargs)
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\cbook\deprecation.py in wrapper(*args, **kwargs)
356 f"%(removal)s. If any parameter follows {name!r}, they "
357 f"should be pass as keyword, not positionally.")
--> 358 return func(*args, **kwargs)
359
360 return wrapper
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\cbook\deprecation.py in wrapper(*args, **kwargs)
356 f"%(removal)s. If any parameter follows {name!r}, they "
357 f"should be pass as keyword, not positionally.")
--> 358 return func(*args, **kwargs)
359
360 return wrapper
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes\_axes.py in imshow(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, shape, filternorm, filterrad, imlim, resample, url, **kwargs)
5624 resample=resample, **kwargs)
5625
-> 5626 im.set_data(X)
5627 im.set_alpha(alpha)
5628 if im.get_clip_path() is None:
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\image.py in set_data(self, A)
691 if (self._A.dtype != np.uint8 and
692 not np.can_cast(self._A.dtype, float, "same_kind")):
--> 693 raise TypeError("Image data of dtype {} cannot be converted to "
694 "float".format(self._A.dtype))
695
TypeError: Image data of dtype object cannot be converted to float