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feat(api): add util to extract metadata from image
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108
invokeai/app/api/extract_metadata_from_image.py
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108
invokeai/app/api/extract_metadata_from_image.py
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import json
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import logging
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from dataclasses import dataclass
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from PIL import Image
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from invokeai.app.services.shared.graph import Graph
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from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutIDValidator
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@dataclass
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class ExtractedMetadata:
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invokeai_metadata: str | None
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invokeai_workflow: str | None
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invokeai_graph: str | None
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def extract_metadata_from_image(
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pil_image: Image.Image,
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invokeai_metadata_override: str | None,
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invokeai_workflow_override: str | None,
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invokeai_graph_override: str | None,
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logger: logging.Logger,
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) -> ExtractedMetadata:
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"""
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Extracts the "invokeai_metadata", "invokeai_workflow", and "invokeai_graph" data embedded in the PIL Image.
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These items are stored as stringified JSON in the image file's metadata, so we need to do some parsing to validate
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them. Once parsed, the values are returned as they came (as strings), or None if they are not present or invalid.
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In some situations, we may prefer to override the values extracted from the image file with some other values.
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For example, when uploading an image via API, the client can optionally provide the metadata directly in the request,
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as opposed to embedding it in the image file. In this case, the client-provided metadata will be used instead of the
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metadata embedded in the image file.
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Args:
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pil_image: The PIL Image object.
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invokeai_metadata_override: The metadata override provided by the client.
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invokeai_workflow_override: The workflow override provided by the client.
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invokeai_graph_override: The graph override provided by the client.
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logger: The logger to use for debug logging.
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Returns:
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ExtractedMetadata: The extracted metadata, workflow, and graph.
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"""
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# The fallback value for metadata is None.
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stringified_metadata: str | None = None
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# Use the metadata override if provided, else attempt to extract it from the image file.
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metadata_raw = invokeai_metadata_override or pil_image.info.get("invokeai_metadata", None)
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# If the metadata is present in the image file, we will attempt to parse it as JSON. When we create images,
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# we always store metadata as a stringified JSON dict. So, we expect it to be a string here.
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if isinstance(metadata_raw, str):
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try:
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# Must be a JSON string
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metadata_parsed = json.loads(metadata_raw)
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# Must be a dict
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if isinstance(metadata_parsed, dict):
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# Looks good, overwrite the fallback value
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stringified_metadata = metadata_raw
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except Exception as e:
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logger.debug(f"Failed to parse metadata for uploaded image, {e}")
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pass
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# We expect the workflow, if embedded in the image, to be a JSON-stringified WorkflowWithoutID. We will store it
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# as a string.
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workflow_raw: str | None = invokeai_workflow_override or pil_image.info.get("invokeai_workflow", None)
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# The fallback value for workflow is None.
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stringified_workflow: str | None = None
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# If the workflow is present in the image file, we will attempt to parse it as JSON. When we create images, we
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# always store workflows as a stringified JSON WorkflowWithoutID. So, we expect it to be a string here.
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if isinstance(workflow_raw, str):
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try:
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# Validate the workflow JSON before storing it
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WorkflowWithoutIDValidator.validate_json(workflow_raw)
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# Looks good, overwrite the fallback value
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stringified_workflow = workflow_raw
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except Exception:
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logger.debug("Failed to parse workflow for uploaded image")
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pass
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# We expect the workflow, if embedded in the image, to be a JSON-stringified Graph. We will store it as a
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# string.
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graph_raw: str | None = invokeai_graph_override or pil_image.info.get("invokeai_graph", None)
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# The fallback value for graph is None.
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stringified_graph: str | None = None
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# If the graph is present in the image file, we will attempt to parse it as JSON. When we create images, we
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# always store graphs as a stringified JSON Graph. So, we expect it to be a string here.
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if isinstance(graph_raw, str):
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try:
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# Validate the graph JSON before storing it
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Graph.model_validate_json(graph_raw)
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# Looks good, overwrite the fallback value
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stringified_graph = graph_raw
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except Exception as e:
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logger.debug(f"Failed to parse graph for uploaded image, {e}")
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pass
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return ExtractedMetadata(
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invokeai_metadata=stringified_metadata, invokeai_workflow=stringified_workflow, invokeai_graph=stringified_graph
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)
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