2023-04-29 14:48:50 +00:00
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# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
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2023-05-21 10:24:37 +00:00
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from logging import Logger
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2023-05-17 09:13:53 +00:00
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from invokeai.app.services.images import ImageService
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remove factory pattern
Factory pattern is now removed. Typical usage of the InvokeAIGenerator is now:
```
from invokeai.backend.generator import (
InvokeAIGeneratorBasicParams,
Txt2Img,
Img2Img,
Inpaint,
)
params = InvokeAIGeneratorBasicParams(
model_name = 'stable-diffusion-1.5',
steps = 30,
scheduler = 'k_lms',
cfg_scale = 8.0,
height = 640,
width = 640
)
print ('=== TXT2IMG TEST ===')
txt2img = Txt2Img(manager, params)
outputs = txt2img.generate(prompt='banana sushi', iterations=2)
for i in outputs:
print(f'image={output.image}, seed={output.seed}, model={output.params.model_name}, hash={output.model_hash}, steps={output.params.steps}')
```
The `params` argument is optional, so if you wish to accept default
parameters and selectively override them, just do this:
```
outputs = Txt2Img(manager).generate(prompt='banana sushi',
steps=50,
scheduler='k_heun',
model_name='stable-diffusion-2.1'
)
```
2023-03-11 00:33:04 +00:00
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from invokeai.backend import ModelManager
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2023-03-03 06:02:00 +00:00
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from .events import EventServiceBase
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2023-04-06 04:06:05 +00:00
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from .latent_storage import LatentsStorageBase
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2023-05-21 10:05:33 +00:00
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from .image_file_storage import ImageFileStorageBase
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2023-03-11 22:00:00 +00:00
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from .restoration_services import RestorationServices
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2023-02-25 04:11:28 +00:00
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from .invocation_queue import InvocationQueueABC
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from .item_storage import ItemStorageABC
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2023-05-04 02:30:30 +00:00
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from .config import InvokeAISettings
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2023-05-17 09:13:53 +00:00
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2023-03-03 06:02:00 +00:00
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class InvocationServices:
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"""Services that can be used by invocations"""
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events: EventServiceBase
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latents: LatentsStorageBase
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images: ImageFileStorageBase
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queue: InvocationQueueABC
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model_manager: ModelManager
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restoration: RestorationServices
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configuration: InvokeAISettings
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2023-05-17 09:13:53 +00:00
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images_new: ImageService
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2023-02-25 04:11:28 +00:00
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# NOTE: we must forward-declare any types that include invocations, since invocations can use services
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graph_library: ItemStorageABC["LibraryGraph"]
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graph_execution_manager: ItemStorageABC["GraphExecutionState"]
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processor: "InvocationProcessorABC"
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def __init__(
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self,
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model_manager: ModelManager,
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events: EventServiceBase,
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logger: Logger,
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latents: LatentsStorageBase,
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2023-05-21 10:05:33 +00:00
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images: ImageFileStorageBase,
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2023-05-17 09:13:53 +00:00
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queue: InvocationQueueABC,
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images_new: ImageService,
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graph_library: ItemStorageABC["LibraryGraph"],
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graph_execution_manager: ItemStorageABC["GraphExecutionState"],
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processor: "InvocationProcessorABC",
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restoration: RestorationServices,
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configuration: InvokeAISettings=None,
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2022-12-01 05:33:20 +00:00
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):
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remove factory pattern
Factory pattern is now removed. Typical usage of the InvokeAIGenerator is now:
```
from invokeai.backend.generator import (
InvokeAIGeneratorBasicParams,
Txt2Img,
Img2Img,
Inpaint,
)
params = InvokeAIGeneratorBasicParams(
model_name = 'stable-diffusion-1.5',
steps = 30,
scheduler = 'k_lms',
cfg_scale = 8.0,
height = 640,
width = 640
)
print ('=== TXT2IMG TEST ===')
txt2img = Txt2Img(manager, params)
outputs = txt2img.generate(prompt='banana sushi', iterations=2)
for i in outputs:
print(f'image={output.image}, seed={output.seed}, model={output.params.model_name}, hash={output.model_hash}, steps={output.params.steps}')
```
The `params` argument is optional, so if you wish to accept default
parameters and selectively override them, just do this:
```
outputs = Txt2Img(manager).generate(prompt='banana sushi',
steps=50,
scheduler='k_heun',
model_name='stable-diffusion-2.1'
)
```
2023-03-11 00:33:04 +00:00
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self.model_manager = model_manager
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self.events = events
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self.logger = logger
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2023-04-06 04:06:05 +00:00
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self.latents = latents
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self.images = images
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self.queue = queue
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self.images_new = images_new
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self.graph_library = graph_library
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self.graph_execution_manager = graph_execution_manager
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self.processor = processor
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self.restoration = restoration
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self.configuration = configuration
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2023-05-17 09:13:53 +00:00
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