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upd SampleGenerator

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This commit is contained in:
Colombo 2020-02-27 09:58:46 +04:00
parent 1898bd6881
commit 9860a38907
4 changed files with 42 additions and 33 deletions
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41
samplelib/SampleProcessor.py
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@ -63,11 +63,14 @@ class SampleProcessor(object):
}
@staticmethod
def process (samples, sample_process_options, output_sample_types, debug, ct_sample=None):
def process (samples, sample_process_options, output_sample_types, debug, ct_sample=None, rnd_state=None):
SPTF = SampleProcessor.Types
sample_rnd_seed = np.random.randint(0x80000000)
if rnd_state is None:
rnd_state = np.random.RandomState( np.random.randint(0x80000000) )
sample_rnd_seed = rnd_state.randint(0x80000000)
outputs = []
for sample in samples:
sample_bgr = sample.load_bgr()
@ -79,7 +82,7 @@ class SampleProcessor(object):
if debug and is_face_sample:
LandmarksProcessor.draw_landmarks (sample_bgr, sample.landmarks, (0, 1, 0))
params = imagelib.gen_warp_params(sample_bgr, sample_process_options.random_flip, rotation_range=sample_process_options.rotation_range, scale_range=sample_process_options.scale_range, tx_range=sample_process_options.tx_range, ty_range=sample_process_options.ty_range, rnd_seed=sample_rnd_seed )
params = imagelib.gen_warp_params(sample_bgr, sample_process_options.random_flip, rotation_range=sample_process_options.rotation_range, scale_range=sample_process_options.scale_range, tx_range=sample_process_options.tx_range, ty_range=sample_process_options.ty_range, rnd_state=rnd_state )
outputs_sample = []
for opts in output_sample_types:
@ -186,10 +189,10 @@ class SampleProcessor(object):
chance, mb_max_size = motion_blur
chance = np.clip(chance, 0, 100)
rnd_state = np.random.RandomState (sample_rnd_seed)
mblur_rnd_chance = rnd_state.randint(100)
mblur_rnd_kernel = rnd_state.randint(mb_max_size)+1
mblur_rnd_deg = rnd_state.randint(360)
l_rnd_state = np.random.RandomState (sample_rnd_seed)
mblur_rnd_chance = l_rnd_state.randint(100)
mblur_rnd_kernel = l_rnd_state.randint(mb_max_size)+1
mblur_rnd_deg = l_rnd_state.randint(360)
if mblur_rnd_chance < chance:
img = imagelib.LinearMotionBlur (img, mblur_rnd_kernel, mblur_rnd_deg )
@ -198,9 +201,9 @@ class SampleProcessor(object):
chance, kernel_max_size = gaussian_blur
chance = np.clip(chance, 0, 100)
rnd_state = np.random.RandomState (sample_rnd_seed+1)
gblur_rnd_chance = rnd_state.randint(100)
gblur_rnd_kernel = rnd_state.randint(kernel_max_size)*2+1
l_rnd_state = np.random.RandomState (sample_rnd_seed+1)
gblur_rnd_chance = l_rnd_state.randint(100)
gblur_rnd_kernel = l_rnd_state.randint(kernel_max_size)*2+1
if gblur_rnd_chance < chance:
img = cv2.GaussianBlur(img, (gblur_rnd_kernel,) *2 , 0)
@ -260,22 +263,22 @@ class SampleProcessor(object):
if mode_type == SPTF.MODE_BGR:
out_sample = img
elif mode_type == SPTF.MODE_BGR_SHUFFLE:
rnd_state = np.random.RandomState (sample_rnd_seed)
out_sample = np.take (img, rnd_state.permutation(img.shape[-1]), axis=-1)
l_rnd_state = np.random.RandomState (sample_rnd_seed)
out_sample = np.take (img, l_rnd_state.permutation(img.shape[-1]), axis=-1)
elif mode_type == SPTF.MODE_BGR_RANDOM_HSV_SHIFT:
rnd_state = np.random.RandomState (sample_rnd_seed)
l_rnd_state = np.random.RandomState (sample_rnd_seed)
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
h, s, v = cv2.split(hsv)
h = (h + rnd_state.randint(360) ) % 360
s = np.clip ( s + rnd_state.random()-0.5, 0, 1 )
v = np.clip ( v + rnd_state.random()-0.5, 0, 1 )
h = (h + l_rnd_state.randint(360) ) % 360
s = np.clip ( s + l_rnd_state.random()-0.5, 0, 1 )
v = np.clip ( v + l_rnd_state.random()-0.5, 0, 1 )
hsv = cv2.merge([h, s, v])
out_sample = np.clip( cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) , 0, 1 )
elif mode_type == SPTF.MODE_BGR_RANDOM_RGB_LEVELS:
rnd_state = np.random.RandomState (sample_rnd_seed)
np_rnd = rnd_state.rand
l_rnd_state = np.random.RandomState (sample_rnd_seed)
np_rnd = l_rnd_state.rand
inBlack = np.array([np_rnd()*0.25 , np_rnd()*0.25 , np_rnd()*0.25], dtype=np.float32)
inWhite = np.array([1.0-np_rnd()*0.25, 1.0-np_rnd()*0.25, 1.0-np_rnd()*0.25], dtype=np.float32)