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Added TileResampler ControlNet preprocessor node.

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Also fixes to SegmentAnything ControlNet preprocessor node.
This commit is contained in:
user1 2023-06-26 04:27:26 -07:00
parent 10e8389fa4
commit 873c18bc4b
1 changed files with 42 additions and 3 deletions
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45
invokeai/app/invocations/controlnet_image_processors.py
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@ -1,8 +1,9 @@
# InvokeAI nodes for ControlNet image preprocessors
# Invocations for ControlNet image preprocessors
# initial implementation by Gregg Helt, 2023
# heavily leverages controlnet_aux package: https://github.com/patrickvonplaten/controlnet_aux
from builtins import float, bool
import cv2
import numpy as np
from typing import Literal, Optional, Union, List, Dict
from PIL import Image, ImageFilter, ImageOps
@ -33,7 +34,7 @@ from controlnet_aux import (
# LeresDetector,
)
from controlnet_aux.util import ade_palette
from controlnet_aux.util import HWC3, ade_palette
from .image import ImageOutput, PILInvocationConfig
@ -483,6 +484,43 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation, PILInvocationCo
# image_resolution=self.image_resolution)
# return processed_image
class TileResamplerProcessorInvocation(ImageProcessorInvocation, PILInvocationConfig):
# fmt: off
type: Literal["tile_image_processor"] = "tile_image_processor"
# Inputs
#res: int = Field(default=512, ge=0, le=1024, description="The pixel resolution for each tile")
down_sampling_rate: float = Field(default=1.0, ge=1.0, le=8.0, description="Down sampling rate")
# fmt: on
# tile_resample copied from sd-webui-controlnet/scripts/processor.py
def tile_resample(self,
np_img: np.ndarray,
res=512, # never used?
down_sampling_rate=1.0,
):
np_img = HWC3(np_img)
if down_sampling_rate < 1.1:
return np_img
H, W, C = np_img.shape
H = int(float(H) / float(down_sampling_rate))
W = int(float(W) / float(down_sampling_rate))
np_img = cv2.resize(np_img, (W, H), interpolation=cv2.INTER_AREA)
return np_img
def run_processor(self, img):
np_img = np.array(img, dtype=np.uint8)
processed_np_image = self.tile_resample(np_img,
#res=self.tile_size,
down_sampling_rate=self.down_sampling_rate
)
processed_image = Image.fromarray(processed_np_image)
return processed_image
class SegmentAnythingProcessorInvocation(ImageProcessorInvocation, PILInvocationConfig):
"""Applies segment anything processing to image"""
# fmt: off
@ -492,7 +530,8 @@ class SegmentAnythingProcessorInvocation(ImageProcessorInvocation, PILInvocation
def run_processor(self, image):
# segment_anything_processor = SamDetector.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints")
segment_anything_processor = SamDetectorReproducibleColors.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints")
processed_image = segment_anything_processor(image)
np_img = np.array(image, dtype=np.uint8)
processed_image = segment_anything_processor(np_img)
return processed_image
class SamDetectorReproducibleColors(SamDetector):