86 lines
3.1 KiB
Python
86 lines
3.1 KiB
Python
import base64
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import hashlib
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import json
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import random
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import uuid
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from flask import Flask, request, jsonify
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import sys
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import openpose_gen as opg
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sys.path.append('./')
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app = Flask(__name__)
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@app.route('/gen_image', methods=['POST'])
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def gen_image():
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if request.is_json:
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data = request.get_json()
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coordinates = data['coordinates']
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canvas_size = data['canvas_size']
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pid = data['pid']
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if not coordinates or not canvas_size:
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return jsonify({"status": "error", "message": "Missing data"}), 422
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openpose_image_path = opg.save_bodypose(canvas_size[0], canvas_size[1], coordinates, pid)
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# gen_fencer_prompt(openpose_image_path, pid, opg.server_address)
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return jsonify({"status": "success", "message": "Data received"}), 201
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else:
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return jsonify({"status": "error", "message": "Request must be JSON"}), 415
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@app.route('/gen_group_pic', methods=['POST'])
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def gen_group_pic():
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if request.is_json:
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data = request.get_json()
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coordinates_list = data['coordinates_list']
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canvas_size = data['canvas_size']
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pid = data['pid']
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base_image = base64.b64decode(data['base_image'])
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if not coordinates_list or not canvas_size or not base_image or not pid:
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return jsonify({"status": "error", "message": "Missing data"}), 422
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for i in range(len(coordinates_list)):
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coordinates_list[i] = coordinates_list[i]['coordinates']
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openpose_image_path = opg.save_bodypose_mulit(canvas_size[0], canvas_size[1], coordinates_list, pid)
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gen_group_pic_prompt(openpose_image_path, base_image, pid, opg.server_address)
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return jsonify({"status": "success", "message": "Data received"}), 201
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else:
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return jsonify({"status": "error", "message": "Request must be JSON"}), 415
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def gen_fencer_prompt(openpose_image_path, pid, comfyUI_address):
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with open("fencerAPI.json", "r") as f:
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prompt_json = f.read()
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prompt = json.loads(prompt_json)
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openpose_image_name = opg.upload_image_circular_queue(openpose_image_path, 20, pid, comfyUI_address)
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opg.upload_image("ref_black.png", "ref_black.png")
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prompt["3"]["inputs"]["seed"] = random.randint(0, 10000000000)
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prompt["29"]["inputs"]['image'] = "ref_black.png"
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prompt["17"]["inputs"]['image'] = openpose_image_name
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opg.queue_prompt(prompt, comfyUI_address)
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def gen_group_pic_prompt(openpose_image_path, base_image, pid, comfyUI_address):
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with open("group_pic.json", "r") as f:
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prompt_json = f.read()
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prompt = json.loads(prompt_json)
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openpose_image_name = opg.upload_image_circular_queue(openpose_image_path, 30, pid, comfyUI_address)
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base_image_name = opg.upload_image_circular_queue(base_image, 30, pid, comfyUI_address)
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prompt["3"]["inputs"]["seed"] = random.randint(0, 10000000000)
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prompt["10"]["inputs"]['image'] = openpose_image_name
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prompt["14"]["inputs"]['image'] = base_image_name
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opg.queue_prompt(prompt, comfyUI_address)
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if __name__ == '__main__':
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app.run(debug=True) |