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https://github.com/invoke-ai/InvokeAI.git
synced 2026-04-23 03:00:31 -04:00
Merges development
This commit is contained in:
psychedelicious
@@ -5,6 +5,8 @@ import shutil
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import mimetypes
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import traceback
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import math
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import io
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import base64
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from flask import Flask, redirect, send_from_directory
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from flask_socketio import SocketIO
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@@ -64,10 +66,7 @@ class InvokeAIWebServer:
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__name__, static_url_path='', static_folder='../frontend/dist/'
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)
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self.socketio = SocketIO(
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self.app,
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**socketio_args
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)
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self.socketio = SocketIO(self.app, **socketio_args)
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# Keep Server Alive Route
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@self.app.route('/flaskwebgui-keep-server-alive')
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@@ -102,6 +101,7 @@ class InvokeAIWebServer:
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close_server_on_exit = False
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try:
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from flaskwebgui import FlaskUI
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FlaskUI(
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app=self.app,
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socketio=self.socketio,
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@@ -186,11 +186,14 @@ class InvokeAIWebServer:
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for path in image_paths:
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metadata = retrieve_metadata(path)
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(width, height) = Image.open(path).size
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image_array.append(
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{
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'url': self.get_url_from_image_path(path),
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'mtime': os.path.getmtime(path),
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'metadata': metadata['sd-metadata'],
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'width': width,
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'height': height,
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}
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)
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@@ -233,11 +236,16 @@ class InvokeAIWebServer:
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for path in image_paths:
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metadata = retrieve_metadata(path)
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(width, height) = Image.open(path).size
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image_array.append(
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{
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'url': self.get_url_from_image_path(path),
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'mtime': os.path.getmtime(path),
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'metadata': metadata['sd-metadata'],
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'width': width,
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'height': height,
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}
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)
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@@ -260,11 +268,24 @@ class InvokeAIWebServer:
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generation_parameters, esrgan_parameters, facetool_parameters
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):
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try:
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print(
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f'>> Image generation requested: {generation_parameters}\nESRGAN parameters: {esrgan_parameters}\nFacetool parameters: {facetool_parameters}'
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)
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# truncate long init_mask base64 if needed
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if 'init_mask' in generation_parameters:
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printable_parameters = {
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**generation_parameters,
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'init_mask': generation_parameters['init_mask'][:20]
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+ '...',
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}
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print(
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f'>> Image generation requested: {printable_parameters}\nESRGAN parameters: {esrgan_parameters}\nFacetool parameters: {facetool_parameters}'
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)
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else:
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print(
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f'>> Image generation requested: {generation_parameters}\nESRGAN parameters: {esrgan_parameters}\nFacetool parameters: {facetool_parameters}'
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)
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self.generate_images(
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generation_parameters, esrgan_parameters, facetool_parameters
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generation_parameters,
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esrgan_parameters,
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facetool_parameters,
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)
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except Exception as e:
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self.socketio.emit('error', {'message': (str(e))})
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@@ -321,16 +342,24 @@ class InvokeAIWebServer:
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elif postprocessing_parameters['type'] == 'gfpgan':
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image = self.gfpgan.process(
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image=image,
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strength=postprocessing_parameters['facetool_strength'],
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strength=postprocessing_parameters[
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'facetool_strength'
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],
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seed=seed,
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)
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elif postprocessing_parameters['type'] == 'codeformer':
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image = self.codeformer.process(
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image=image,
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strength=postprocessing_parameters['facetool_strength'],
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fidelity=postprocessing_parameters['codeformer_fidelity'],
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strength=postprocessing_parameters[
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'facetool_strength'
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],
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fidelity=postprocessing_parameters[
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'codeformer_fidelity'
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],
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seed=seed,
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device='cpu' if str(self.generate.device) == 'mps' else self.generate.device
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device='cpu'
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if str(self.generate.device) == 'mps'
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else self.generate.device,
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)
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else:
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raise TypeError(
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@@ -349,6 +378,8 @@ class InvokeAIWebServer:
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command = parameters_to_command(postprocessing_parameters)
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(width, height) = image.size
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path = self.save_result_image(
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image,
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command,
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@@ -371,6 +402,8 @@ class InvokeAIWebServer:
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'url': self.get_url_from_image_path(path),
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'mtime': os.path.getmtime(path),
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'metadata': metadata,
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'width': width,
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'height': height,
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},
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)
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except Exception as e:
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@@ -482,19 +515,41 @@ class InvokeAIWebServer:
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if 'init_img' in generation_parameters:
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init_img_url = generation_parameters['init_img']
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generation_parameters[
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'init_img'
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] = self.get_image_path_from_url(
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generation_parameters['init_img']
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)
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init_img_path = self.get_image_path_from_url(init_img_url)
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generation_parameters['init_img'] = init_img_path
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# if 'init_mask' in generation_parameters:
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# mask_img_url = generation_parameters['init_mask']
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# generation_parameters[
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# 'init_mask'
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# ] = self.get_image_path_from_url(
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# generation_parameters['init_mask']
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# )
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if 'init_mask' in generation_parameters:
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mask_img_url = generation_parameters['init_mask']
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generation_parameters[
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'init_mask'
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] = self.get_image_path_from_url(
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generation_parameters['init_mask']
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# grab an Image of the init image
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original_image = Image.open(init_img_path)
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# copy a region from it which we will inpaint
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cropped_init_image = copy_image_from_bounding_box(
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original_image, **generation_parameters['bounding_box']
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)
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generation_parameters['init_img'] = cropped_init_image
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# grab an Image of the mask
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mask_image = Image.open(
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io.BytesIO(
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base64.decodebytes(
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bytes(generation_parameters['init_mask'], 'utf-8')
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)
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)
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)
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# crop the mask image
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cropped_mask_image = copy_image_from_bounding_box(
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mask_image, **generation_parameters['bounding_box']
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)
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generation_parameters['init_mask'] = cropped_mask_image
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totalSteps = self.calculate_real_steps(
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steps=generation_parameters['steps'],
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@@ -532,6 +587,8 @@ class InvokeAIWebServer:
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)
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command = parameters_to_command(generation_parameters)
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(width, height) = image.size
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path = self.save_result_image(
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image,
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command,
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@@ -548,6 +605,8 @@ class InvokeAIWebServer:
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'url': self.get_url_from_image_path(path),
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'mtime': os.path.getmtime(path),
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'metadata': metadata,
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'width': width,
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'height': height
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},
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)
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self.socketio.emit(
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@@ -625,7 +684,9 @@ class InvokeAIWebServer:
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if facetool_parameters['type'] == 'gfpgan':
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progress.set_current_status('Restoring Faces (GFPGAN)')
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elif facetool_parameters['type'] == 'codeformer':
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progress.set_current_status('Restoring Faces (Codeformer)')
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progress.set_current_status(
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'Restoring Faces (Codeformer)'
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)
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progress.set_current_status_has_steps(False)
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self.socketio.emit(
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@@ -643,11 +704,17 @@ class InvokeAIWebServer:
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image = self.codeformer.process(
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image=image,
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strength=facetool_parameters['strength'],
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fidelity=facetool_parameters['codeformer_fidelity'],
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fidelity=facetool_parameters[
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'codeformer_fidelity'
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],
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seed=seed,
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device='cpu' if str(self.generate.device) == 'mps' else self.generate.device,
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device='cpu'
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if str(self.generate.device) == 'mps'
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else self.generate.device,
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)
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all_parameters['codeformer_fidelity'] = facetool_parameters['codeformer_fidelity']
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all_parameters[
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'codeformer_fidelity'
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] = facetool_parameters['codeformer_fidelity']
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postprocessing = True
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all_parameters['facetool_strength'] = facetool_parameters[
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@@ -663,12 +730,20 @@ class InvokeAIWebServer:
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)
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eventlet.sleep(0)
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# paste the inpainting image back onto the original
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if 'init_mask' in generation_parameters:
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image = paste_image_into_bounding_box(
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Image.open(init_img_path),
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image,
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**generation_parameters['bounding_box'],
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)
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# restore the stashed URLS and discard the paths, we are about to send the result to client
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if 'init_img' in all_parameters:
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all_parameters['init_img'] = init_img_url
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if 'init_mask' in all_parameters:
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all_parameters['init_mask'] = mask_img_url
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all_parameters['init_mask'] = '' #
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metadata = self.parameters_to_generated_image_metadata(
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all_parameters
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@@ -676,6 +751,8 @@ class InvokeAIWebServer:
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command = parameters_to_command(all_parameters)
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(width, height) = image.size
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path = self.save_result_image(
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image,
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command,
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@@ -705,6 +782,8 @@ class InvokeAIWebServer:
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'url': self.get_url_from_image_path(path),
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'mtime': os.path.getmtime(path),
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'metadata': metadata,
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'width': width,
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'height': height,
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},
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)
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eventlet.sleep(0)
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@@ -766,12 +845,14 @@ class InvokeAIWebServer:
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# 'postprocessing' is either null or an
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if 'facetool_strength' in parameters:
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facetool_parameters = {
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'type': str(parameters['facetool_type']),
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'strength': float(parameters['facetool_strength']),
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}
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'type': str(parameters['facetool_type']),
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'strength': float(parameters['facetool_strength']),
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}
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if parameters['facetool_type'] == 'codeformer':
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facetool_parameters['fidelity'] = float(parameters['codeformer_fidelity'])
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facetool_parameters['fidelity'] = float(
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parameters['codeformer_fidelity']
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)
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postprocessing.append(facetool_parameters)
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@@ -792,7 +873,9 @@ class InvokeAIWebServer:
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rfc_dict['sampler'] = parameters['sampler_name']
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# display weighted subprompts (liable to change)
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subprompts = split_weighted_subprompts(parameters['prompt'], skip_normalize=True)
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subprompts = split_weighted_subprompts(
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parameters['prompt'], skip_normalize=True
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)
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subprompts = [{'prompt': x[0], 'weight': x[1]} for x in subprompts]
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rfc_dict['prompt'] = subprompts
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@@ -817,13 +900,13 @@ class InvokeAIWebServer:
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rfc_dict['init_image_path'] = parameters[
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'init_img'
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] # TODO: Noncompliant
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if 'init_mask' in parameters:
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rfc_dict['mask_hash'] = calculate_init_img_hash(
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self.get_image_path_from_url(parameters['init_mask'])
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) # TODO: Noncompliant
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rfc_dict['mask_image_path'] = parameters[
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'init_mask'
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] # TODO: Noncompliant
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# if 'init_mask' in parameters:
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# rfc_dict['mask_hash'] = calculate_init_img_hash(
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# self.get_image_path_from_url(parameters['init_mask'])
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# ) # TODO: Noncompliant
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# rfc_dict['mask_image_path'] = parameters[
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# 'init_mask'
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# ] # TODO: Noncompliant
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else:
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rfc_dict['type'] = 'txt2img'
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@@ -875,7 +958,9 @@ class InvokeAIWebServer:
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postprocessing_metadata['strength'] = parameters[
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'facetool_strength'
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]
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postprocessing_metadata['fidelity'] = parameters['codeformer_fidelity']
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postprocessing_metadata['fidelity'] = parameters[
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'codeformer_fidelity'
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]
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else:
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raise TypeError(f"Invalid type: {parameters['type']}")
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@@ -1119,3 +1204,29 @@ class Progress:
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class CanceledException(Exception):
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pass
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"""
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Crops an image to a bounding box.
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"""
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def copy_image_from_bounding_box(image, x, y, width, height):
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with image as im:
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bounds = (x, y, x + width, y + height)
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im_cropped = im.crop(bounds)
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return im_cropped
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"""
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Pastes an image onto another with a bounding box.
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"""
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def paste_image_into_bounding_box(
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recipient_image, donor_image, x, y, width, height
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):
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with recipient_image as im:
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bounds = (x, y, x + width, y + height)
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im.paste(donor_image, bounds)
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return recipient_image
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