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feat: add checkpoint metadata to EXIF recipe data

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Add support for storing checkpoint information in image EXIF metadata. The checkpoint data is simplified and includes fields like model ID, version, name, hash, and base model. This allows for better tracking of AI model checkpoints used in image generation workflows.
This commit is contained in:
Will Miao
2025-11-29 08:46:38 +08:00
parent 073fb3a94a
commit df93670598
2 changed files with 86 additions and 2 deletions
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27
py/utils/exif_utils.py
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@@ -140,6 +140,28 @@ class ExifUtils:
if metadata:
# Remove any existing recipe metadata
metadata = ExifUtils.remove_recipe_metadata(metadata)
# Prepare checkpoint data
checkpoint_data = recipe_data.get("checkpoint") or {}
simplified_checkpoint = None
if isinstance(checkpoint_data, dict) and checkpoint_data:
simplified_checkpoint = {
"type": checkpoint_data.get("type", "checkpoint"),
"modelId": checkpoint_data.get("modelId", 0),
"modelVersionId": checkpoint_data.get("modelVersionId")
or checkpoint_data.get("id", 0),
"modelName": checkpoint_data.get(
"modelName", checkpoint_data.get("name", "")
),
"modelVersionName": checkpoint_data.get(
"modelVersionName", checkpoint_data.get("version", "")
),
"hash": checkpoint_data.get("hash", "").lower()
if checkpoint_data.get("hash")
else "",
"file_name": checkpoint_data.get("file_name", ""),
"baseModel": checkpoint_data.get("baseModel", ""),
}
# Prepare simplified loras data
simplified_loras = []
@@ -160,7 +182,8 @@ class ExifUtils:
'base_model': recipe_data.get('base_model', ''),
'loras': simplified_loras,
'gen_params': recipe_data.get('gen_params', {}),
'tags': recipe_data.get('tags', [])
'tags': recipe_data.get('tags', []),
**({'checkpoint': simplified_checkpoint} if simplified_checkpoint else {})
}
# Convert to JSON string
@@ -359,4 +382,4 @@ class ExifUtils:
return f.read(), os.path.splitext(image_data)[1]
except Exception:
return image_data, '.jpg' # Last resort fallback
return image_data, '.jpg'
return image_data, '.jpg'