mirror of
https://github.com/immich-app/immich.git
synced 2025-11-03 19:29:32 -05:00
87a0ba3db3
* export clip models * export to hf refactored export code * export mclip, general refactoring cleanup * updated conda deps * do transforms with pillow and numpy, add tokenization config to export, general refactoring * moved conda dockerfile, re-added poetry * minor fixes * updated link * updated tests * removed `requirements.txt` from workflow * fixed mimalloc path * removed torchvision * cleaner np typing * review suggestions * update default model name * update test
41 lines
837 B
Python
41 lines
837 B
Python
from enum import StrEnum
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from typing import TypeAlias
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import numpy as np
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from pydantic import BaseModel
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def to_lower_camel(string: str) -> str:
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tokens = [token.capitalize() if i > 0 else token for i, token in enumerate(string.split("_"))]
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return "".join(tokens)
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class TextModelRequest(BaseModel):
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text: str
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class TextResponse(BaseModel):
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__root__: str
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class MessageResponse(BaseModel):
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message: str
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class BoundingBox(BaseModel):
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x1: int
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y1: int
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x2: int
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y2: int
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class ModelType(StrEnum):
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IMAGE_CLASSIFICATION = "image-classification"
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CLIP = "clip"
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FACIAL_RECOGNITION = "facial-recognition"
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ndarray_f32: TypeAlias = np.ndarray[int, np.dtype[np.float32]]
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ndarray_i64: TypeAlias = np.ndarray[int, np.dtype[np.int64]]
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ndarray_i32: TypeAlias = np.ndarray[int, np.dtype[np.int32]]
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