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removing default yaw_value from DFLIMG files,

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added better pitch/yaw estimator from 68 landmarks,
improving face yaw accuracy for sorting and trainers,
added sort by face-pitch
This commit is contained in:
iperov 2019-02-12 21:31:37 +04:00
parent 535041f7bb
commit 06fe1314d8
13 changed files with 182 additions and 37 deletions
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29
samples/SampleGeneratorFace.py
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@ -4,6 +4,7 @@ import random
import cv2
import multiprocessing
from utils import iter_utils
from facelib import LandmarksProcessor
from samples import SampleType
from samples import SampleProcessor
@ -18,11 +19,13 @@ output_sample_types = [
]
'''
class SampleGeneratorFace(SampleGeneratorBase):
def __init__ (self, samples_path, debug, batch_size, sort_by_yaw=False, sort_by_yaw_target_samples_path=None, with_close_to_self=False, sample_process_options=SampleProcessor.Options(), output_sample_types=[], add_sample_idx=False, generators_count=2, **kwargs):
def __init__ (self, samples_path, debug, batch_size, sort_by_yaw=False, sort_by_yaw_target_samples_path=None, with_close_to_self=False, sample_process_options=SampleProcessor.Options(), output_sample_types=[], add_sample_idx=False, add_pitch=False, add_yaw=False, generators_count=2, **kwargs):
super().__init__(samples_path, debug, batch_size)
self.sample_process_options = sample_process_options
self.output_sample_types = output_sample_types
self.add_sample_idx = add_sample_idx
self.add_pitch = add_pitch
self.add_yaw = add_yaw
if sort_by_yaw_target_samples_path is not None:
self.sample_type = SampleType.FACE_YAW_SORTED_AS_TARGET
@ -131,17 +134,33 @@ class SampleGeneratorFace(SampleGeneratorBase):
if type(x) != tuple and type(x) != list:
raise Exception('SampleProcessor.process returns NOT tuple/list')
if batches is None:
batches = [ [] for _ in range(len(x)) ]
if self.add_sample_idx:
batches += [ [] ]
i_sample_idx = len(batches)-1
if self.add_pitch:
batches += [ [] ]
i_pitch = len(batches)-1
if self.add_yaw:
batches += [ [] ]
i_yaw = len(batches)-1
for i in range(len(x)):
batches[i].append ( x[i] )
if self.add_sample_idx:
batches[-1].append (idx)
batches[i_sample_idx].append (idx)
if self.add_pitch or self.add_yaw:
pitch, yaw = LandmarksProcessor.estimate_pitch_yaw (sample.landmarks)
if self.add_pitch:
batches[i_pitch].append (pitch)
if self.add_yaw:
batches[i_yaw].append (yaw)
break
yield [ np.array(batch) for batch in batches]