import gradio as gr import numpy as np import cv2 from fastapi import FastAPI, Request, Response from src.body import Body body_estimation = Body('model/body_pose_model.pth') def pil2cv(image): ''' PIL型 -> OpenCV型 ''' new_image = np.array(image, dtype=np.uint8) if new_image.ndim == 2: # モノクロ pass elif new_image.shape[2] == 3: # カラー new_image = cv2.cvtColor(new_image, cv2.COLOR_RGB2BGR) elif new_image.shape[2] == 4: # 透過 new_image = cv2.cvtColor(new_image, cv2.COLOR_RGBA2BGRA) return new_image with open("static/poseEditor.js", "r") as f: file_contents = f.read() app = FastAPI() @app.middleware("http") async def some_fastapi_middleware(request: Request, call_next): path = request.scope['path'] # get the request route response = await call_next(request) if path == "/": response_body = "" async for chunk in response.body_iterator: response_body += chunk.decode() some_javascript = f""" """ response_body = response_body.replace("", some_javascript + "") del response.headers["content-length"] return Response( content=response_body, status_code=response.status_code, headers=dict(response.headers), media_type=response.media_type ) return response # make cndidate to json def candidate_to_json_string(arr): a = [f'[{x:.2f}, {y:.2f}]' for x, y, *_ in arr] return '[' + ', '.join(a) + ']' # make subset to json def subset_to_json_string(arr): arr_str = ','.join(['[' + ','.join([f'{num:.2f}' for num in row]) + ']' for row in arr]) return '[' + arr_str + ']' def estimate_body(source): print("estimate_body") if source == None: return None candidate, subset = body_estimation(pil2cv(source)) print(candidate_to_json_string(candidate)) print(subset_to_json_string(subset)) return "{ \"candidate\": " + candidate_to_json_string(candidate) + ", \"subset\": " + subset_to_json_string(subset) + " }" def image_changed(image): if (image == None): return None json = estimate_body(image) return json, image.width, image.height html_text = f""" """ with gr.Blocks() as demo: with gr.Row(): with gr.Column(scale=1): source = gr.Image(type="pil") width = gr.Slider(label="Width", mininmum=512, maximum=1024, step=64, value=512, key="Width", interactive=True) height = gr.Slider(label="Height", mininmum=512, maximum=1024, step=64, value=512, key="Height", interactive=True) startBtn = gr.Button(value="Start edit") json = gr.JSON(label="Body") with gr.Column(scale=2): gr.HTML("") html = gr.HTML(html_text) saveBtn = gr.Button(value="Save") source.change( fn = image_changed, inputs = [source], outputs = [json, width, height]) startBtn.click( fn = None, inputs = [json, width, height], outputs = [], _js="(json, w, h) => { initializePose(json,w,h); return []; }") saveBtn.click( fn = None, inputs = [], outputs = [], _js="() => { savePose(); }") gr.mount_gradio_app(app, demo, path="/")