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lama_cleaner
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remove scikit-image

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Qing 2023-04-16 10:27:39 +08:00
parent 95245425eb
commit 0d89c37ef1
2 changed files with 20 additions and 15 deletions
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34
lama_cleaner/model/zits.py
View File

@ -2,8 +2,6 @@ import os
import time
import cv2
import skimage
from skimage import color, feature
import torch
import torch.nn.functional as F
@ -170,15 +168,19 @@ def load_image(img, mask, device, sigma256=3.0):
# https://scikit-image.org/docs/stable/api/skimage.feature.html#skimage.feature.canny
# low_threshold: Lower bound for hysteresis thresholding (linking edges). If None, low_threshold is set to 10% of dtype’s max.
# high_threshold: Upper bound for hysteresis thresholding (linking edges). If None, high_threshold is set to 20% of dtype’s max.
gray_256 = color.rgb2gray(img_256)
edge_256 = feature.canny(gray_256, sigma=sigma256, mask=None).astype(float)
# cv2.imwrite("skimage_gray.jpg", (_gray_256*255).astype(np.uint8))
# cv2.imwrite("skimage_edge.jpg", (_edge_256*255).astype(np.uint8))
# gray_256 = cv2.cvtColor(img_256, cv2.COLOR_RGB2GRAY)
# gray_256_blured = cv2.GaussianBlur(gray_256, ksize=(3,3), sigmaX=sigma256, sigmaY=sigma256)
# edge_256 = cv2.Canny(gray_256_blured, threshold1=int(255*0.1), threshold2=int(255*0.2))
# cv2.imwrite("edge.jpg", edge_256)
try:
import skimage
gray_256 = skimage.color.rgb2gray(img_256)
edge_256 = skimage.feature.canny(gray_256, sigma=3.0, mask=None).astype(float)
# cv2.imwrite("skimage_gray.jpg", (gray_256*255).astype(np.uint8))
# cv2.imwrite("skimage_edge.jpg", (edge_256*255).astype(np.uint8))
except:
gray_256 = cv2.cvtColor(img_256, cv2.COLOR_RGB2GRAY)
gray_256_blured = cv2.GaussianBlur(gray_256, ksize=(7, 7), sigmaX=sigma256, sigmaY=sigma256)
edge_256 = cv2.Canny(gray_256_blured, threshold1=int(255*0.1), threshold2=int(255*0.2))
# cv2.imwrite("opencv_edge.jpg", edge_256)
# line
img_512 = resize(img, 512, 512)
@ -381,10 +383,14 @@ class ZITS(InpaintModel):
for line, score in zip(lines_masked, scores_masked):
if score > mask_th:
rr, cc, value = skimage.draw.line_aa(
*to_int(line[0:2]), *to_int(line[2:4])
)
lmap[rr, cc] = np.maximum(lmap[rr, cc], value)
try:
import skimage
rr, cc, value = skimage.draw.line_aa(
*to_int(line[0:2]), *to_int(line[2:4])
)
lmap[rr, cc] = np.maximum(lmap[rr, cc], value)
except:
cv2.line(lmap, to_int(line[0:2][::-1]), to_int(line[2:4][::-1]), (1, 1, 1), 1, cv2.LINE_AA)
lmap = np.clip(lmap * 255, 0, 255).astype(np.uint8)
lines_tensor.append(to_tensor(lmap).unsqueeze(0))

1
requirements.txt
View File

@ -11,7 +11,6 @@ loguru
pytest
yacs
markupsafe==2.0.1
scikit-image==0.19.3
diffusers[torch]==0.14.0
transformers==4.27.4
gradio