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fix(api): reduce copies, fix function signatures

This commit is contained in:
Sean Sube 2023-01-15 11:09:47 -06:00
parent ef06b45599
commit f5ed77a349
2 changed files with 41 additions and 39 deletions
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47
api/onnx_web/image.py
View File

@ -13,21 +13,6 @@ def blend_imult(a):
return 1.0 - blend_mult(a)
def blend_mask_source(source: Tuple[int, int, int], mask: Tuple[int, int, int], noise: Tuple[int, int, int]) -> Tuple[int, int, int]:
'''
Blend operation, linear interpolation from noise to source based on mask: `(s * (1 - m)) + (n * m)`
Black = noise
White = source
'''
return (
int((source[0] * blend_mult(mask[0])) +
(noise[0] * blend_imult(mask[0]))),
int((source[1] * blend_mult(mask[1])) +
(noise[1] * blend_imult(mask[1]))),
int((source[2] * blend_mult(mask[2])) +
(noise[2] * blend_imult(mask[2]))),
)
def blend_source_mask(source: Tuple[int, int, int], mask: Tuple[int, int, int], noise: Tuple[int, int, int]) -> Tuple[int, int, int]:
'''
Blend operation, linear interpolation from source to noise based on mask: `(s * (1 - m)) + (n * m)`
@ -44,14 +29,20 @@ def blend_source_mask(source: Tuple[int, int, int], mask: Tuple[int, int, int],
)
def mask_filter_gaussian(mask_image: Image, dims: Tuple[int, int], origin: Tuple[int, int], rounds=3) -> Tuple[float, float, float]:
def mask_filter_none(mask_image: Image, dims: Tuple[int, int], origin: Tuple[int, int], fill='white') -> Image:
width, height = dims
noise = Image.new('RGB', (width, height), fill)
noise.paste(mask_image, origin)
return noise
def mask_filter_gaussian(mask_image: Image, dims: Tuple[int, int], origin: Tuple[int, int], rounds=3) -> Image:
'''
Gaussian blur, source image centered on white canvas.
'''
width, height = dims
noise = Image.new('RGB', (width, height), 'white')
noise.paste(mask_image, origin)
noise = mask_filter_none(mask_image, dims, origin)
for i in range(rounds):
blur = noise.filter(ImageFilter.GaussianBlur(5))
@ -60,7 +51,7 @@ def mask_filter_gaussian(mask_image: Image, dims: Tuple[int, int], origin: Tuple
return noise
def noise_source_fill(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int], fill='white') -> Tuple[float, float, float]:
def noise_source_fill(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int], fill='white') -> Image:
'''
Identity transform, source image centered on white canvas.
'''
@ -72,7 +63,7 @@ def noise_source_fill(source_image: Image, dims: Tuple[int, int], origin: Tuple[
return noise
def noise_source_gaussian(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int], rounds=3) -> Tuple[float, float, float]:
def noise_source_gaussian(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int], rounds=3) -> Image:
'''
Gaussian blur, source image centered on white canvas.
'''
@ -85,7 +76,7 @@ def noise_source_gaussian(source_image: Image, dims: Tuple[int, int], origin: Tu
return noise
def noise_source_uniform(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int]) -> Tuple[float, float, float]:
def noise_source_uniform(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int]) -> Image:
width, height = dims
size = width * height
@ -107,7 +98,7 @@ def noise_source_uniform(source_image: Image, dims: Tuple[int, int], origin: Tup
return noise
def noise_source_normal(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int]) -> Tuple[float, float, float]:
def noise_source_normal(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int]) -> Image:
width, height = dims
size = width * height
@ -129,7 +120,7 @@ def noise_source_normal(source_image: Image, dims: Tuple[int, int], origin: Tupl
return noise
def noise_source_histogram(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int]) -> Tuple[float, float, float]:
def noise_source_histogram(source_image: Image, dims: Tuple[int, int], origin: Tuple[int, int]) -> Image:
r, g, b = source_image.split()
width, height = dims
size = width * height
@ -180,9 +171,9 @@ def expand_image(
full_source = Image.new('RGB', dims, fill)
full_source.paste(source_image, origin)
full_mask = Image.new('RGB', dims, fill)
full_mask = mask_filter_gaussian(full_mask, dims, origin)
full_mask.paste(mask_image, origin)
full_mask = mask_filter(mask_image, dims, origin)
# full_mask = Image.new('RGB', dims, fill)
# full_mask.paste(mask_image, origin)
full_noise = noise_source(source_image, dims, origin)

33
api/onnx_web/serve.py
View File

@ -29,7 +29,18 @@ from struct import pack
from os import environ, makedirs, path, scandir
from typing import Any, Dict, Tuple, Union
from .image import expand_image, noise_source_gaussian, noise_source_histogram, noise_source_normal, noise_source_fill, noise_source_uniform, blend_source_mask, blend_imult, blend_mask_source, blend_mult
from .image import (
expand_image,
# mask filters
mask_filter_gaussian,
mask_filter_none,
# noise sources
noise_source_gaussian,
noise_source_histogram,
noise_source_normal,
noise_source_fill,
noise_source_uniform,
)
import json
import numpy as np
@ -79,9 +90,9 @@ noise_sources = {
'normal': noise_source_normal,
'uniform': noise_source_uniform,
}
blend_modes = {
'mask-source': blend_mask_source,
'source-mask': blend_source_mask,
mask_filters = {
'none': mask_filter_none,
'gaussian': mask_filter_gaussian,
}
@ -294,7 +305,7 @@ def run_inpaint_pipeline(
top: int,
bottom: int,
noise_source: Any,
blend_op: Any
mask_filter: Any
):
pipe = load_pipeline(OnnxStableDiffusionInpaintPipeline,
model, provider, scheduler)
@ -309,7 +320,7 @@ def run_inpaint_pipeline(
mask_image,
(left, right, top, bottom),
noise_source=noise_source,
blend_op=blend_op)
mask_filter=mask_filter)
if environ.get('DEBUG') is not None:
source_image.save('./last-source.png')
@ -391,9 +402,9 @@ def introspect():
}
@app.route('/api/settings/blends')
def list_blend_sources():
return jsonify(list(blend_modes.keys()))
@app.route('/api/settings/masks')
def list_mask_filters():
return jsonify(list(mask_filters.keys()))
@app.route('/api/settings/models')
@ -505,9 +516,9 @@ def inpaint():
bottom = get_and_clamp_int(
request.args, 'bottom', 0, config_params.get('height').get('max'), 0)
mask_filter= get_from_map(request.args, 'filter', mask_filters, 'none')
noise_source = get_from_map(
request.args, 'noise', noise_sources, 'histogram')
blend_op = get_from_map(request.args, 'blend', blend_modes, 'mask-source')
(output_file, output_full) = make_output_path(
'inpaint', seed, (prompt, cfg, steps, height, width, seed, left, right, top, bottom))
@ -536,7 +547,7 @@ def inpaint():
top,
bottom,
noise_source,
blend_op)
mask_filter)
return jsonify({
'output': output_file,