82 lines
2.9 KiB
Python
82 lines
2.9 KiB
Python
import numpy as np
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from fastapi import FastAPI, Body
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from fastapi.exceptions import HTTPException
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from PIL import Image
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import gradio as gr
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from modules.api.models import *
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from modules.api import api
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from scripts import external_code, global_state
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def encode_to_base64(image):
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if type(image) is str:
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return image
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elif type(image) is Image.Image:
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return api.encode_pil_to_base64(image)
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elif type(image) is np.ndarray:
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return encode_np_to_base64(image)
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else:
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return ""
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def encode_np_to_base64(image):
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pil = Image.fromarray(image)
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return api.encode_pil_to_base64(pil)
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def controlnet_api(_: gr.Blocks, app: FastAPI):
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@app.get("/controlnet/version")
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async def version():
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return {"version": external_code.get_api_version()}
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@app.get("/controlnet/model_list")
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async def model_list():
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up_to_date_model_list = external_code.get_models(update=True)
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print(up_to_date_model_list)
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return {"model_list": up_to_date_model_list}
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@app.get("/controlnet/module_list")
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async def module_list(alias_names: bool = False):
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_module_list = external_code.get_modules(alias_names)
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print(_module_list)
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return {"module_list": _module_list}
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@app.post("/controlnet/detect")
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async def detect(
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controlnet_module: str = Body("none", title='Controlnet Module'),
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controlnet_input_images: List[str] = Body([], title='Controlnet Input Images'),
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controlnet_processor_res: int = Body(512, title='Controlnet Processor Resolution'),
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controlnet_threshold_a: float = Body(64, title='Controlnet Threshold a'),
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controlnet_threshold_b: float = Body(64, title='Controlnet Threshold b')
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):
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controlnet_module = global_state.reverse_preprocessor_aliases.get(controlnet_module, controlnet_module)
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if controlnet_module not in global_state.cn_preprocessor_modules:
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raise HTTPException(
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status_code=422, detail="Module not available")
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if len(controlnet_input_images) == 0:
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raise HTTPException(
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status_code=422, detail="No image selected")
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print(f"Detecting {str(len(controlnet_input_images))} images with the {controlnet_module} module.")
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results = []
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processor_module = global_state.cn_preprocessor_modules[controlnet_module]
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for input_image in controlnet_input_images:
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img = external_code.to_base64_nparray(input_image)
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results.append(processor_module(img, res=controlnet_processor_res, thr_a=controlnet_threshold_a, thr_b=controlnet_threshold_b)[0])
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global_state.cn_preprocessor_unloadable.get(controlnet_module, lambda: None)()
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results64 = list(map(encode_to_base64, results))
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return {"images": results64, "info": "Success"}
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try:
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import modules.script_callbacks as script_callbacks
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script_callbacks.on_app_started(controlnet_api)
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except:
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pass
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