enhancing landmarks extractor by using s3fd second pass inside second pass,

it will be x2 slower, but time will be saved due to more images will be marked properly
works on 2GB+
This commit is contained in:
iperov 2019-03-18 10:25:24 +04:00
parent 1d56585f33
commit b8efb4cbba
3 changed files with 51 additions and 17 deletions

View file

@ -3,7 +3,8 @@ import numpy as np
import os
import cv2
from pathlib import Path
from facelib import FaceType
from facelib import LandmarksProcessor
class LandmarksExtractor(object):
def __init__ (self, keras):
@ -23,7 +24,7 @@ class LandmarksExtractor(object):
del self.keras_model
return False #pass exception between __enter__ and __exit__ to outter level
def extract_from_bgr (self, input_image, rects):
def extract_from_bgr (self, input_image, rects, second_pass_extractor=None):
input_image = input_image[:,:,::-1].copy()
(h, w, ch) = input_image.shape
@ -44,10 +45,29 @@ class LandmarksExtractor(object):
landmarks.append ( ( (left, top, right, bottom),pts_img ) )
except Exception as e:
print ("extract_from_bgr: ", traceback.format_exc() )
landmarks.append ( ( (left, top, right, bottom), [ (0,0) for _ in range(68) ] ) )
landmarks.append ( ( (left, top, right, bottom), None ) )
if second_pass_extractor is not None:
for i in range(len(landmarks)):
rect, lmrks = landmarks[i]
if lmrks is None:
continue
image_to_face_mat = LandmarksProcessor.get_transform_mat (lmrks, 256, FaceType.FULL)
face_image = cv2.warpAffine(input_image, image_to_face_mat, (256, 256), cv2.INTER_CUBIC)
rects2 = second_pass_extractor.extract_from_bgr(face_image)
if len(rects2) != 1: #dont do second pass if more than 1 face detected in cropped image
continue
rect2 = rects2[0]
lmrks2 = self.extract_from_bgr (face_image, [rect2] )[0][1]
source_lmrks2 = LandmarksProcessor.transform_points (lmrks2, image_to_face_mat, True)
landmarks[i] = (rect, source_lmrks2)
return landmarks
def transform(self, point, center, scale, resolution):
pt = np.array ( [point[0], point[1], 1.0] )
h = 200.0 * scale