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stage3_5.py
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stage3_5.py
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import cv2
import os
import glob
import shutil
import numpy as np
from PIL import Image
from color_matcher import ColorMatcher
from color_matcher.normalizer import Normalizer
def resize_img(img, w, h):
if img.shape[0] + img.shape[1] < h + w:
interpolation = interpolation=cv2.INTER_CUBIC
else:
interpolation = interpolation=cv2.INTER_AREA
return cv2.resize(img, (w, h), interpolation=interpolation)
def get_pair_of_img(img_path, target_dir):
img_basename = os.path.basename(img_path)
target_path = os.path.join( target_dir , img_basename )
return target_path if os.path.isfile( target_path ) else None
def remove_pngs_in_dir(path):
if not os.path.isdir(path):
return
pngs = glob.glob( os.path.join(path, "*.png") )
for png in pngs:
os.remove(png)
def get_pair_of_img(img, target_dir):
img_basename = os.path.basename(img)
pair_path = os.path.join( target_dir , img_basename )
if os.path.isfile( pair_path ):
return pair_path
print("!!! pair of "+ img + " not in " + target_dir)
return ""
def get_mask_array(mask_path):
if not mask_path:
return None
mask_array = np.asarray(Image.open( mask_path ))
if mask_array.ndim == 2:
mask_array = mask_array[:, :, np.newaxis]
mask_array = mask_array[:,:,:1]
mask_array = mask_array/255
return mask_array
def color_match(imgs, ref_image, color_matcher_method, dst_path):
cm = ColorMatcher(method=color_matcher_method)
i = 0
total = len(imgs)
for fname in imgs:
img_src = Image.open(fname)
img_src = Normalizer(np.asarray(img_src)).type_norm()
img_src = cm.transfer(src=img_src, ref=ref_image, method=color_matcher_method)
img_src = Normalizer(img_src).uint8_norm()
Image.fromarray(img_src).save(os.path.join(dst_path, os.path.basename(fname)))
i += 1
print("{0}/{1}".format(i, total))
imgs = sorted( glob.glob( os.path.join(dst_path, "*.png") ) )
def ebsynth_utility_stage3_5(dbg, project_args, color_matcher_method, st3_5_use_mask, st3_5_use_mask_ref, st3_5_use_mask_org, color_matcher_ref_type, color_matcher_ref_image):
dbg.print("stage3.5")
dbg.print("")
_, _, frame_path, frame_mask_path, org_key_path, img2img_key_path, _ = project_args
backup_path = os.path.join( os.path.join( img2img_key_path, "..") , "st3_5_backup_img2img_key")
backup_path = os.path.normpath(backup_path)
if not os.path.isdir( backup_path ):
dbg.print("{0} not found -> create backup.".format(backup_path))
os.makedirs(backup_path, exist_ok=True)
imgs = glob.glob( os.path.join(img2img_key_path, "*.png") )
for img in imgs:
img_basename = os.path.basename(img)
pair_path = os.path.join( backup_path , img_basename )
shutil.copy( img , pair_path)
else:
dbg.print("{0} found -> Treat the images here as originals.".format(backup_path))
org_imgs = sorted( glob.glob( os.path.join(backup_path, "*.png") ) )
head_of_keyframe = org_imgs[0]
# open ref img
ref_image = color_matcher_ref_image
if not ref_image:
dbg.print("color_matcher_ref_image not set")
if color_matcher_ref_type == 0:
#'original video frame'
dbg.print("select -> original video frame")
ref_image = Image.open( get_pair_of_img(head_of_keyframe, frame_path) )
else:
#'first frame of img2img result'
dbg.print("select -> first frame of img2img result")
ref_image = Image.open( get_pair_of_img(head_of_keyframe, backup_path) )
ref_image = np.asarray(ref_image)
if st3_5_use_mask_ref:
mask = get_pair_of_img(head_of_keyframe, frame_mask_path)
if mask:
mask_array = get_mask_array( mask )
ref_image = ref_image * mask_array
ref_image = ref_image.astype(np.uint8)
else:
dbg.print("select -> color_matcher_ref_image")
ref_image = np.asarray(ref_image)
if color_matcher_method in ('mvgd', 'hm-mvgd-hm'):
sample_img = Image.open(head_of_keyframe)
ref_image = resize_img( ref_image, sample_img.width, sample_img.height )
ref_image = Normalizer(ref_image).type_norm()
if st3_5_use_mask_org:
tmp_path = os.path.join( os.path.join( img2img_key_path, "..") , "st3_5_tmp")
tmp_path = os.path.normpath(tmp_path)
dbg.print("create {0} for masked original image".format(tmp_path))
remove_pngs_in_dir(tmp_path)
os.makedirs(tmp_path, exist_ok=True)
for org_img in org_imgs:
image_basename = os.path.basename(org_img)
org_image = np.asarray(Image.open(org_img))
mask = get_pair_of_img(org_img, frame_mask_path)
if mask:
mask_array = get_mask_array( mask )
org_image = org_image * mask_array
org_image = org_image.astype(np.uint8)
Image.fromarray(org_image).save( os.path.join( tmp_path, image_basename ) )
org_imgs = sorted( glob.glob( os.path.join(tmp_path, "*.png") ) )
color_match(org_imgs, ref_image, color_matcher_method, img2img_key_path)
if st3_5_use_mask or st3_5_use_mask_org:
imgs = sorted( glob.glob( os.path.join(img2img_key_path, "*.png") ) )
for img in imgs:
mask = get_pair_of_img(img, frame_mask_path)
if mask:
mask_array = get_mask_array( mask )
bg = get_pair_of_img(img, frame_path)
bg_image = np.asarray(Image.open( bg ))
fg_image = np.asarray(Image.open( img ))
final_img = fg_image * mask_array + bg_image * (1-mask_array)
final_img = final_img.astype(np.uint8)
Image.fromarray(final_img).save(img)
dbg.print("")
dbg.print("completed.")