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https://github.com/invoke-ai/InvokeAI
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50bef87da7
Metadata for the Linear UI is now sneakily provided via a `MetadataAccumulator` node, which the client populates / hooks up while building the graph.
Additionally, we provide the unexpanded graph with the metadata API response.
Both of these are embedded into the PNGs.
- Remove `metadata` from `ImageDTO`
- Split up the `images/` routes to accomodate this; metadata is only retrieved per-image
- `images/{image_name}` now gets the DTO
- `images/{image_name}/metadata` gets the new metadata
- `images/{image_name}/full` gets the full-sized image file
- Remove old metadata service
- Add `MetadataAccumulator` node, `CoreMetadataField`, hook up to `LatentsToImage` node
- Add `get_raw()` method to `ItemStorage`, retrieves the row from DB as a string, no pydantic parsing
- Update `images`related services to handle storing and retrieving the new metadata
- Add `get_metadata_graph_from_raw_session` which extracts the `graph` from `session` without needing to hydrate the session in pydantic, in preparation for providing it as metadata; also removes all references to the `MetadataAccumulator` node
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| .. | ||
| __init__.py | ||
| baseinvocation.py | ||
| collections.py | ||
| compel.py | ||
| controlnet_image_processors.py | ||
| cv.py | ||
| generate.py | ||
| image.py | ||
| infill.py | ||
| latent.py | ||
| math.py | ||
| metadata.py | ||
| model.py | ||
| noise.py | ||
| param_easing.py | ||
| params.py | ||
| prompt.py | ||
| reconstruct.py | ||
| upscale.py | ||