Delete modules

modules/diffusers_modules/local/block.py

@@ -1,96 +0,0 @@
-from diffusers.modular_pipelines import (
-    PipelineBlock,
-    InputParam,
-    OutputParam,
-    ConfigSpec,
-)
-
-from diffusers.utils import load_image
-from PIL import Image
-from typing import Union, Tuple
-
-# copied from https://github.com/Wan-Video/Wan2.2/blob/388807310646ed5f318a99f8e8d9ad28c5b65373/wan/utils/utils.py#L136
-def best_output_size(w, h, dw, dh, expected_area):
-    # float output size
-    ratio = w / h
-    ow = (expected_area * ratio)**0.5
-    oh = expected_area / ow
-
-    # process width first
-    ow1 = int(ow // dw * dw)
-    oh1 = int(expected_area / ow1 // dh * dh)
-    assert ow1 % dw == 0 and oh1 % dh == 0 and ow1 * oh1 <= expected_area
-    ratio1 = ow1 / oh1
-
-    # process height first
-    oh2 = int(oh // dh * dh)
-    ow2 = int(expected_area / oh2 // dw * dw)
-    assert oh2 % dh == 0 and ow2 % dw == 0 and ow2 * oh2 <= expected_area
-    ratio2 = ow2 / oh2
-
-    # compare ratios
-    if max(ratio / ratio1, ratio1 / ratio) < max(ratio / ratio2,
-                                                 ratio2 / ratio):
-        return ow1, oh1
-    else:
-        return ow2, oh2
-
-class Wan225BI2VImageProcessor(PipelineBlock):
-
-    @property
-    def description(self):
-        return "default Image Processor for wan2.2 5b i2v, it resizes the image to the best output size and center-crop it"
-
-    @property
-    def inputs(self):
-        return [
-            InputParam(name="image", type_hint=Union[Image.Image, str], description= "the Image to process"),
-            InputParam(name="max_area", type_hint=int, description= "the maximum area of the Image to process")
-        ]
-    
-    @property
-    def intermediate_outputs(self):
-        return [
-            OutputParam(name="processed_image", type_hint=Image.Image, description= "the processed Image"),
-        ]
-    
-    @property
-    def expected_configs(self):
-        return [
-            ConfigSpec(name="patch_size", default=(1, 2, 2)),
-            ConfigSpec(name="vae_stride", default=(4, 16, 16)),
-        ]
-    
-    def __call__(self, components, state):
-
-        block_state = self.get_block_state(state)
-
-        if isinstance(block_state.image, str):
-            image = load_image(block_state.image).convert("RGB")
-        elif isinstance(block_state.image, Image.Image):
-            image = block_state.image
-        else:
-            raise ValueError(f"Invalid image type: {type(block_state.image)}; only support PIL Image or url string")
-        
-        ih, iw = image.height, image.width
-        dh, dw = components.config.patch_size[1] * components.config.vae_stride[1], components.config.patch_size[2] * components.config.vae_stride[2]
-        ow, oh = best_output_size(iw, ih, dw, dh, block_state.max_area)
-
-        scale = max(ow / iw, oh / ih)
-        resized_image = image.resize((round(iw * scale), round(ih * scale)), Image.LANCZOS)
-
-        # center-crop
-        x1 = (resized_image.width - ow) // 2
-        y1 = (resized_image.height - oh) // 2
-        cropped_image = resized_image.crop((x1, y1, x1 + ow, y1 + oh))
-        assert cropped_image.width == ow and cropped_image.height == oh
-
-        block_state.processed_image = cropped_image
-
-        print(f" initial image size: {image.size}")
-        print(f" processed image size: {cropped_image.size}")
-        
-
-        self.set_block_state(state, block_state)
-        return components, state
-