mirror of
https://github.com/storytold/storyteller-ml.git
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salt
106 lines
3.0 KiB
Python
106 lines
3.0 KiB
Python
import os
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import cv2
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import numpy as np
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from flow.flow_utils import flow_calc, read_flow, read_mask
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class BaseGuide:
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def __init__(self):
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...
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def get_cmd(self, i, weight) -> str:
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return (f'-guide {os.path.abspath(self.imgs[0])} '
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f'{os.path.abspath(self.imgs[i])} -weight {weight}')
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class ColorGuide(BaseGuide):
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def __init__(self, imgs):
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super().__init__()
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self.imgs = imgs
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class PositionalGuide(BaseGuide):
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def __init__(self, flow_paths, save_paths):
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super().__init__()
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flows = [read_flow(f) for f in flow_paths]
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masks = [read_mask(f) for f in flow_paths]
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# TODO: modify the format of flow to numpy
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H, W = flows[0].shape[2:]
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first_img = PositionalGuide.__generate_first_img(H, W)
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prev_img = first_img
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imgs = [first_img]
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cid = 0
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for flow, mask in zip(flows, masks):
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cur_img = flow_calc.warp(prev_img, flow,
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'nearest').astype(np.uint8)
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cur_img = cv2.inpaint(cur_img, mask, 30, cv2.INPAINT_TELEA)
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prev_img = cur_img
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imgs.append(cur_img)
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cid += 1
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cv2.imwrite(f'guide/{cid}.jpg', mask)
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for path, img in zip(save_paths, imgs):
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cv2.imwrite(path, img)
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self.imgs = save_paths
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@staticmethod
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def __generate_first_img(H, W):
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Hs = np.linspace(0, 1, H)
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Ws = np.linspace(0, 1, W)
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i, j = np.meshgrid(Hs, Ws, indexing='ij')
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r = (i * 255).astype(np.uint8)
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g = (j * 255).astype(np.uint8)
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b = np.zeros(r.shape)
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res = np.stack((b, g, r), 2)
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return res
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class EdgeGuide(BaseGuide):
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def __init__(self, imgs, save_paths):
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super().__init__()
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edges = [EdgeGuide.__generate_edge(cv2.imread(img)) for img in imgs]
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for path, img in zip(save_paths, edges):
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cv2.imwrite(path, img)
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self.imgs = save_paths
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@staticmethod
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def __generate_edge(img):
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filter = np.array([[0, -1, 0], [-1, 4, -1], [0, -1, 0]])
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res = cv2.filter2D(img, -1, filter)
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return res
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class TemporalGuide(BaseGuide):
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def __init__(self, key_img, stylized_imgs, flow_paths, save_paths):
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super().__init__()
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self.flows = [read_flow(f) for f in flow_paths]
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self.masks = [read_mask(f) for f in flow_paths]
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self.stylized_imgs = stylized_imgs
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self.imgs = save_paths
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first_img = cv2.imread(key_img)
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cv2.imwrite(self.imgs[0], first_img)
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def get_cmd(self, i, weight) -> str:
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if i == 0:
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warped_img = self.stylized_imgs[0]
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else:
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prev_img = cv2.imread(self.stylized_imgs[i - 1])
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warped_img = flow_calc.warp(prev_img, self.flows[i - 1],
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'nearest').astype(np.uint8)
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warped_img = cv2.inpaint(warped_img, self.masks[i - 1], 30,
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cv2.INPAINT_TELEA)
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cv2.imwrite(self.imgs[i], warped_img)
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return super().get_cmd(i, weight)
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