feat: add outscaling option

README.md

@@ -59,6 +59,7 @@ Based on guides by:
       - [For Nvidia everywhere: Install PyTorch GPU and ONNX GPU](#for-nvidia-everywhere-install-pytorch-gpu-and-onnx-gpu)
     - [Download and convert models](#download-and-convert-models)
     - [Test the models](#test-the-models)
+    - [Upscaling and face correction](#upscaling-and-face-correction)
   - [Usage](#usage)
     - [Running the containers](#running-the-containers)
     - [Configuring and running the server](#configuring-and-running-the-server)
@@ -310,6 +311,13 @@ If the script works, there will be an image of an astronaut in `outputs/test.png
 
 If you get any errors, check [the known errors section](#known-errors-and-solutions).
 
+### Upscaling and face correction
+
+Models:
+
+- https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth
+- https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth
+
 ## Usage
 
 ### Running the containers

api/onnx_web/serve.py

@@ -106,6 +106,12 @@ mask_filters = {
     'gaussian-screen': mask_filter_gaussian_screen,
 }
 
+# TODO: load from model_path
+upscale_models = [
+    'RealESRGAN_x4plus',
+    'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth', # TODO: convert GFPGAN
+]
+
 
 def serve_bundle_file(filename='index.html'):
     return send_from_directory(path.join('..', bundle_path), filename)
@@ -192,9 +198,17 @@ def border_from_request() -> Border:
 def upscale_from_request() -> UpscaleParams:
     denoise = get_and_clamp_float(request.args, 'denoise', 0.5, 1.0, 0.0)
     scale = get_and_clamp_int(request.args, 'scale', 1, 4, 1)
+    outscale = get_and_clamp_int(request.args, 'outscale', 1, 4, 1)
     faces = request.args.get('faces', 'false') == 'true'
-    platform = 'onnx'
+    return UpscaleParams(
-    return UpscaleParams(scale=scale, faces=faces, platform=platform, denoise=denoise)
+        upscale_models[0],
+        scale=scale,
+        outscale=outscale,
+        faces=faces,
+        face_model=upscale_models[1],
+        platform='onnx',
+        denoise=denoise,
+    )
 
 def check_paths():
     if not path.exists(model_path):

api/onnx_web/upscale.py

@@ -1,11 +1,10 @@
 from basicsr.archs.rrdbnet_arch import RRDBNet
-from basicsr.utils.download_util import load_file_from_url
 from gfpgan import GFPGANer
 from onnxruntime import InferenceSession
 from os import path
 from PIL import Image
 from realesrgan import RealESRGANer
-from typing import Any
+from typing import Any, Union
 
 import numpy as np
 import torch
@@ -15,16 +14,9 @@ from .utils import (
 )
 
 # TODO: these should all be params or config
-fp16 = False
-outscale = 4
 pre_pad = 0
 tile_pad = 10
 
-gfpgan_url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth'
-resrgan_name = 'RealESRGAN_x4plus'
-resrgan_url = [
-    'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth']
-
 
 class ONNXImage():
     def __init__(self, source) -> None:
@@ -51,6 +43,9 @@ class ONNXImage():
     def numpy(self):
         return self.source
 
+    def size(self):
+        return np.shape(self.source)
+
 
 class ONNXNet():
     '''
@@ -87,29 +82,44 @@ class ONNXNet():
 
 
 class UpscaleParams():
-    def __init__(self, scale=4, faces=True, platform='onnx', denoise=0.5) -> None:
+    def __init__(
-        self.denoise = denoise
+        self,
+        upscale_model: str,
+        scale: int = 4,
+        outscale: int = 1,
+        denoise: float = 0.5,
+        faces=True,
+        face_model: Union[str, None] = None,
+        platform: str = 'onnx',
+        half=False
+    ) -> None:
+        self.upscale_model = upscale_model
         self.scale = scale
+        self.outscale = outscale
+        self.denoise = denoise
         self.faces = faces
+        self.face_model = face_model
         self.platform = platform
+        self.half = half
 
 
 def make_resrgan(ctx: ServerContext, params: UpscaleParams, tile=0):
-    model_path = path.join(ctx.model_path, resrgan_name + '.pth')
+    model_path = path.join(ctx.model_path, '%s.%s' %
+                           (params.upscale_model, params.platform))
     if not path.isfile(model_path):
-        for url in resrgan_url:
+        raise Exception('Real ESRGAN model not found at %s' % model_path)
-            model_path = load_file_from_url(
-                url=url, model_dir=path.join(model_path, resrgan_name), progress=True, file_name=None)
 
     # use ONNX acceleration, if available
     if params.platform == 'onnx':
         model = ONNXNet(ctx)
-    else:
+    elif params.platform == 'pth':
         model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64,
                         num_block=23, num_grow_ch=32, scale=params.scale)
+    else:
+        raise Exception('unknown platform %s' % params.platform)
 
     dni_weight = None
-    if resrgan_name == 'realesr-general-x4v3' and params.denoise != 1:
+    if params.upscale_model == 'realesr-general-x4v3' and params.denoise != 1:
         wdn_model_path = model_path.replace(
             'realesr-general-x4v3', 'realesr-general-wdn-x4v3')
         model_path = [model_path, wdn_model_path]
@@ -123,7 +133,7 @@ def make_resrgan(ctx: ServerContext, params: UpscaleParams, tile=0):
         tile=tile,
         tile_pad=tile_pad,
         pre_pad=pre_pad,
-        half=fp16)
+        half=params.half)
 
     return upsampler
 
@@ -134,8 +144,7 @@ def upscale_resrgan(ctx: ServerContext, params: UpscaleParams, source_image: Ima
     image = np.array(source_image)
     upsampler = make_resrgan(ctx, params)
 
-    # TODO: what is outscale for here?
+    output, _ = upsampler.enhance(image, outscale=params.outscale)
-    output, _ = upsampler.enhance(image, outscale=outscale)
 
     if params.faces:
         output = upscale_gfpgan(ctx, params, output)
@@ -144,14 +153,18 @@ def upscale_resrgan(ctx: ServerContext, params: UpscaleParams, source_image: Ima
 
 
 def upscale_gfpgan(ctx: ServerContext, params: UpscaleParams, image, upsampler=None) -> Image:
-    print('correcting faces with GFPGAN')
+    print('correcting faces with GFPGAN model: %s' % params.face_model)
+
+    if params.face_model is None:
+        print('no face model given, skipping')
+        return image
 
     if upsampler is None:
         upsampler = make_resrgan(ctx, params, tile=512)
 
     face_enhancer = GFPGANer(
-        model_path=gfpgan_url,
+        model_path=params.face_model,
-        upscale=outscale,
+        upscale=params.outscale,
         arch='clean',
         channel_multiplier=2,
         bg_upsampler=upsampler)

api/params.json

@@ -61,6 +61,12 @@
     "max": 1,
     "step": 0.01
   },
+  "outscale": {
+    "default": 1,
+    "min": 1,
+    "max": 4,
+    "step": 1
+  },
   "width": {
     "default": 512,
     "min": 64,

gui/src/client.ts

@@ -71,6 +71,7 @@ export interface UpscaleParams {
   denoise: number;
   faces: boolean;
   scale: number;
+  outscale: number;
 }
 
 export interface ApiResponse {
@@ -170,6 +171,7 @@ export function appendUpscaleToURL(url: URL, upscale: UpscaleParams) {
   url.searchParams.append('denoise', upscale.denoise.toFixed(FIXED_FLOAT));
   url.searchParams.append('faces', String(upscale.faces));
   url.searchParams.append('scale', upscale.scale.toFixed(FIXED_INTEGER));
+  url.searchParams.append('outscale', upscale.outscale.toFixed(FIXED_INTEGER));
 }
 
 export function makeClient(root: string, f = fetch): ApiClient {

gui/src/components/ImageCard.tsx

@@ -1,5 +1,5 @@
 import { doesExist, mustExist } from '@apextoaster/js-utils';
-import { ContentCopy, ContentCopyTwoTone, Delete, Download } from '@mui/icons-material';
+import { Brush, ContentCopy, ContentCopyTwoTone, Delete, Download } from '@mui/icons-material';
 import { Box, Button, Card, CardContent, CardMedia, Grid, Paper } from '@mui/material';
 import * as React from 'react';
 import { useContext } from 'react';
@@ -86,7 +86,7 @@ export function ImageCard(props: ImageCardProps) {
           </GridItem>
           <GridItem xs={2}>
             <Button onClick={copySourceToInpaint}>
-              <ContentCopyTwoTone />
+              <Brush />
             </Button>
           </GridItem>
           <GridItem xs={2}>

gui/src/components/ImageInput.tsx

@@ -24,7 +24,13 @@ export function ImageInput(props: ImageInputProps) {
     }
 
     if (doesExist(props.image)) {
-      return <img src={URL.createObjectURL(props.image)} />;
+      return <img
+        src={URL.createObjectURL(props.image)}
+        style={{
+          maxWidth: 512,
+          maxHeight: 512,
+        }}
+      />;
     } else {
       return <div>Please select an image.</div>;
     }

gui/src/components/MaskCanvas.tsx

@@ -1,6 +1,6 @@
 import { doesExist, Maybe, mustExist } from '@apextoaster/js-utils';
 import { FormatColorFill, Gradient } from '@mui/icons-material';
-import { Button, Stack } from '@mui/material';
+import { Button, Stack, Typography } from '@mui/material';
 import { throttle } from 'lodash';
 import React, { RefObject, useContext, useEffect, useMemo, useRef, useState } from 'react';
 import { useStore } from 'zustand';
@@ -230,6 +230,9 @@ export function MaskCanvas(props: MaskCanvasProps) {
         }
       }}
     />
+    <Typography variant='body1'>
+      Black pixels in the mask will stay the same, white pixels will be replaced with pixels from the noise source.
+    </Typography>
     <Stack direction='row' spacing={4}>
       <NumericField
         label='Brush Color'

gui/src/components/UpscaleControl.tsx

@@ -48,6 +48,19 @@ export function UpscaleControl(props: UpscaleControlProps) {
         });
       }}
     />
+    <NumericField
+      label='Outscale'
+      disabled={params.enabled === false}
+      min={config.outscale.min}
+      max={config.outscale.max}
+      step={config.outscale.step}
+      value={params.outscale}
+      onChange={(outscale) => {
+        setUpscale({
+          outscale,
+        });
+      }}
+    />
     <NumericField
       label='Denoise'
       decimal

gui/src/state.ts

@@ -241,6 +241,7 @@ export function createStateSlices(base: ConfigParams) {
       enabled: false,
       faces: false,
       scale: 1,
+      outscale: 1,
     },
     setUpscale(upscale) {
       set((prev) => ({

onnx-web.code-workspace

@@ -34,6 +34,7 @@
 			"Onnx",
 			"onnxruntime",
 			"outpaint",
+			"outscale",
 			"pndm",
 			"pretrained",
 			"protobuf",