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manual extractor: added zoom for small faces

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iperov 2019-02-10 22:40:57 +04:00
parent bda3fb3da1
commit 0866b2c509
1 changed files with 22 additions and 4 deletions
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26
mainscripts/Extractor.py
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@ -46,12 +46,13 @@ class ExtractSubprocessor(SubprocessorBase):
self.param_x = -1
self.param_y = -1
self.param_rect_size = -1
self.param = {'x': 0, 'y': 0, 'rect_size' : 5, 'rect_locked' : False, 'redraw_needed' : False }
self.param = {'x': 0, 'y': 0, 'rect_size' : 100, 'rect_locked' : False, 'redraw_needed' : False }
def onMouse(event, x, y, flags, param):
if event == cv2.EVENT_MOUSEWHEEL:
mod = 1 if flags > 0 else -1
param['rect_size'] = max (5, param['rect_size'] + 10*mod)
mod = 1 if flags > 0 else -1
diff = 1 if param['rect_size'] <= 40 else np.clip(param['rect_size'] / 10, 1, 10)
param['rect_size'] = max (5, param['rect_size'] + diff*mod)
elif event == cv2.EVENT_LBUTTONDOWN:
param['rect_locked'] = not param['rect_locked']
param['redraw_needed'] = True
@ -358,9 +359,26 @@ class ExtractSubprocessor(SubprocessorBase):
if self.manual == True:
self.landmarks = result[1][0][1]
image = cv2.addWeighted (self.original_image,1.0,self.text_lines_img,1.0,0)
(h,w,c) = self.original_image.shape
image = cv2.addWeighted (self.original_image,1.0,self.text_lines_img,1.0,0)
view_rect = (np.array(self.rect) * self.view_scale).astype(np.int).tolist()
view_landmarks = (np.array(self.landmarks) * self.view_scale).astype(np.int).tolist()
if self.param_rect_size <= 40:
scaled_rect_size = h // 3 if w > h else w // 3
p1 = (self.param_x - self.param_rect_size // 2, self.param_y - self.param_rect_size // 2)
p2 = (self.param_x + self.param_rect_size // 2, self.param_y - self.param_rect_size // 2)
p3 = (self.param_x - self.param_rect_size // 2, self.param_y + self.param_rect_size // 2)
np1 = (self.param_x - scaled_rect_size // 2, self.param_y - scaled_rect_size // 2)
np2 = (self.param_x + scaled_rect_size // 2, self.param_y - scaled_rect_size // 2)
np3 = (self.param_x - scaled_rect_size // 2, self.param_y + scaled_rect_size // 2)
mat = cv2.getAffineTransform( np.float32([p1,p2,p3])*self.view_scale, np.float32([np1,np2,np3])*self.view_scale )
image = cv2.warpAffine(image, mat,(w,h) )
view_landmarks = LandmarksProcessor.transform_points (view_landmarks, mat)
LandmarksProcessor.draw_rect_landmarks (image, view_rect, view_landmarks, self.image_size, self.face_type)
if self.param['rect_locked']: