fix tile-colorfix problems
This will completely solve problems related to tile-colorfix and now tile colorfix/colorfix+sharp give same results to webui-cn
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@ -615,7 +615,8 @@ legacy_preprocessors = {
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"priority": 100,
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"priority": 100,
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"tags": [
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"tags": [
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"MLSD"
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"MLSD"
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]
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],
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"use_soft_projection_in_hr_fix": True
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},
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},
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# "normal_bae": {
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# "normal_bae": {
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# "label": "normal_bae",
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# "label": "normal_bae",
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@ -59,6 +59,9 @@ class LegacyPreprocessor(Preprocessor):
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'instant-iD': ['instant_id', 'instantid'],
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'instant-iD': ['instant_id', 'instantid'],
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}
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}
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if legacy_dict.get('use_soft_projection_in_hr_fix', False):
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self.use_soft_projection_in_hr_fix = True
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self.model_filename_filters = []
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self.model_filename_filters = []
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for tag in self.tags:
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for tag in self.tags:
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tag_lower = tag.lower()
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tag_lower = tag.lower()
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@ -467,8 +467,11 @@ class ControlNetForForgeOfficial(scripts.Script):
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params.model.positive_advanced_weighting = soft_weighting.copy()
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params.model.positive_advanced_weighting = soft_weighting.copy()
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params.model.negative_advanced_weighting = zero_weighting.copy()
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params.model.negative_advanced_weighting = zero_weighting.copy()
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# high-ref fix pass always use softer injections
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if unit.control_mode == external_code.ControlMode.PROMPT.value:
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if is_hr_pass or unit.control_mode == external_code.ControlMode.PROMPT.value:
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params.model.positive_advanced_weighting = soft_weighting.copy()
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params.model.negative_advanced_weighting = soft_weighting.copy()
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if is_hr_pass and params.preprocessor.use_soft_projection_in_hr_fix:
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params.model.positive_advanced_weighting = soft_weighting.copy()
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params.model.positive_advanced_weighting = soft_weighting.copy()
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params.model.negative_advanced_weighting = soft_weighting.copy()
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params.model.negative_advanced_weighting = soft_weighting.copy()
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@ -32,6 +32,7 @@ class Preprocessor:
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self.sorting_priority = 0 # higher goes to top in the list
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self.sorting_priority = 0 # higher goes to top in the list
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self.corp_image_with_a1111_mask_when_in_img2img_inpaint_tab = True
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self.corp_image_with_a1111_mask_when_in_img2img_inpaint_tab = True
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self.fill_mask_with_one_when_resize_and_fill = False
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self.fill_mask_with_one_when_resize_and_fill = False
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self.use_soft_projection_in_hr_fix = False
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def setup_model_patcher(self, model, load_device=None, offload_device=None, dtype=torch.float32, **kwargs):
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def setup_model_patcher(self, model, load_device=None, offload_device=None, dtype=torch.float32, **kwargs):
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if load_device is None:
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if load_device is None:
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@ -86,6 +87,7 @@ class PreprocessorCanny(Preprocessor):
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self.slider_1 = PreprocessorParameter(minimum=0, maximum=256, step=1, value=100, label='Low Threshold', visible=True)
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self.slider_1 = PreprocessorParameter(minimum=0, maximum=256, step=1, value=100, label='Low Threshold', visible=True)
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self.slider_2 = PreprocessorParameter(minimum=0, maximum=256, step=1, value=200, label='High Threshold', visible=True)
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self.slider_2 = PreprocessorParameter(minimum=0, maximum=256, step=1, value=200, label='High Threshold', visible=True)
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self.sorting_priority = 100
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self.sorting_priority = 100
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self.use_soft_projection_in_hr_fix = True
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def __call__(self, input_image, resolution, slider_1=None, slider_2=None, slider_3=None, **kwargs):
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def __call__(self, input_image, resolution, slider_1=None, slider_2=None, slider_3=None, **kwargs):
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input_image, remove_pad = resize_image_with_pad(input_image, resolution)
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input_image, remove_pad = resize_image_with_pad(input_image, resolution)
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