Add files via upload
This commit is contained in:
taabata
+184
@@ -0,0 +1,184 @@
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from flask import Flask, render_template, request
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from PIL import Image
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import numpy as np
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from flask_cors import CORS
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import os, io, base64, glob, json, time, random
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from urllib import request as rq
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app = Flask(__name__)
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CORS(app)
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@app.route("/")
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def index():
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return render_template("mix.html")
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@app.route("/stickerize",methods=["GET","POST"])
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def stickerize():
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imagedata = request.json["image"]
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pixels = imagedata
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if pixels != "":
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for i in range(0,len(pixels)):
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for j in range(0,len(pixels[i])):
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pixels[i][j] = tuple(pixels[i][j])
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array = np.array(pixels, dtype=np.uint8)
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image = Image.fromarray(array)
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image.save('image1.png')
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list_of_files = glob.glob('../../../output/*')
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latest_file = max(list_of_files, key=os.path.getctime)
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def queue_prompt(prompt_workflow):
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p = {"prompt": prompt_workflow}
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data = json.dumps(p).encode('utf-8')
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req = rq.Request("http://127.0.0.1:8188/prompt", data=data)
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rq.urlopen(req)
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prompt_workflow = json.load(open('./static/stickerize_api.json'))
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prompt_workflow['36']['inputs']['image'] = os.path.join(os.getcwd(),"image1.png")
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prompt_workflow['36']['inputs']['seed'] = random.randint(0,100000)
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queue_prompt(prompt_workflow)
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new_file = latest_file
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while new_file == latest_file:
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list_of_files = glob.glob('../../../output/*')
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new_file = max(list_of_files, key=os.path.getctime)
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time.sleep(1)
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image = Image.open(f'../../../output/{os.path.basename(new_file)}')
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buf = io.BytesIO()
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image.save(buf, format='PNG')
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byte_im = buf.getvalue()
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byte_im = base64.b64encode(byte_im).decode('utf-8')
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byte_im = f"data:image/png;base64,{byte_im}"
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print(byte_im)
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return {"byte_im":byte_im}
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@app.route("/mix",methods=["GET","POST"])
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def mix():
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imagedata1 = request.json["image1"]
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imagedata2 = request.json["image2"]
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setting = request.json["setting"]
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print(setting)
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pixels = imagedata1
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if pixels != "":
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for i in range(0,len(pixels)):
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for j in range(0,len(pixels[i])):
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pixels[i][j] = tuple(pixels[i][j])
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array = np.array(pixels, dtype=np.uint8)
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image = Image.fromarray(array)
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image.save('image1.png')
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pixels = imagedata2
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if pixels != "":
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for i in range(0,len(pixels)):
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for j in range(0,len(pixels[i])):
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pixels[i][j] = tuple(pixels[i][j])
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array = np.array(pixels, dtype=np.uint8)
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image = Image.fromarray(array)
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image.save('image2.png')
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list_of_files = glob.glob('../../../output/*')
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latest_file = max(list_of_files, key=os.path.getctime)
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def queue_prompt(prompt_workflow):
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p = {"prompt": prompt_workflow}
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data = json.dumps(p).encode('utf-8')
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req = rq.Request("http://127.0.0.1:8188/prompt", data=data)
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rq.urlopen(req)
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prompt_workflow = json.load(open('./static/mix_api.json'))
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prompt_workflow['171']['inputs']['image'] = os.path.join(os.getcwd(),"image1.png")
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prompt_workflow['171']['inputs']['seed'] = random.randint(0,100000)
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prompt_workflow['172']['inputs']['image'] = os.path.join(os.getcwd(),"image2.png")
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prompt_workflow['172']['inputs']['seed'] = random.randint(0,100000)
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if setting == 1:
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prompt_workflow['1']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['7']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['83']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['159']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['1']['inputs']['strength'] = 0.75
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prompt_workflow['7']['inputs']['strength'] = 0.75
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prompt_workflow['83']['inputs']['strength'] = 0.75
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prompt_workflow['159']['inputs']['strength'] = 0.75
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prompt_workflow['1']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['7']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['83']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['159']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['1']['inputs']['controlnet_conditioning_scale'] = 0.50
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prompt_workflow['7']['inputs']['controlnet_conditioning_scale'] = 0.50
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prompt_workflow['83']['inputs']['controlnet_conditioning_scale'] = 0.50
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prompt_workflow['159']['inputs']['controlnet_conditioning_scale'] = 0.50
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prompt_workflow['1']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['7']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['83']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['159']['inputs']['seed'] = random.randint(0,1000000000)
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elif setting == 2:
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prompt_workflow['1']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['7']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['83']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['159']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['1']['inputs']['strength'] = 0.75
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prompt_workflow['7']['inputs']['strength'] = 0.75
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prompt_workflow['83']['inputs']['strength'] = 0.75
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prompt_workflow['159']['inputs']['strength'] = 0.75
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prompt_workflow['1']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['7']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['83']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['159']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['1']['inputs']['controlnet_conditioning_scale'] = 0.24
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prompt_workflow['7']['inputs']['controlnet_conditioning_scale'] = 0.24
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prompt_workflow['83']['inputs']['controlnet_conditioning_scale'] = 0.24
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prompt_workflow['159']['inputs']['controlnet_conditioning_scale'] = 0.24
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prompt_workflow['1']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['7']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['83']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['159']['inputs']['seed'] = random.randint(0,1000000000)
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elif setting ==3:
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prompt_workflow['1']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['7']['inputs']['style_fidelity'] = 0.50
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prompt_workflow['83']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['159']['inputs']['style_fidelity'] = 0.99
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prompt_workflow['1']['inputs']['strength'] = 0.75
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prompt_workflow['7']['inputs']['strength'] = 0.75
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prompt_workflow['83']['inputs']['strength'] = 0.75
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prompt_workflow['159']['inputs']['strength'] = 0.75
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prompt_workflow['1']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['7']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['83']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['159']['inputs']['ipadapter_scale'] = 0.80
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prompt_workflow['1']['inputs']['controlnet_conditioning_scale'] = 0.50
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prompt_workflow['7']['inputs']['controlnet_conditioning_scale'] = 0.24
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prompt_workflow['83']['inputs']['controlnet_conditioning_scale'] = 0.50
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prompt_workflow['159']['inputs']['controlnet_conditioning_scale'] = 0.50
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prompt_workflow['1']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['7']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['83']['inputs']['seed'] = random.randint(0,1000000000)
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prompt_workflow['159']['inputs']['seed'] = random.randint(0,1000000000)
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queue_prompt(prompt_workflow)
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new_file = latest_file
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while new_file == latest_file:
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list_of_files = glob.glob('../../../output/*')
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new_file = max(list_of_files, key=os.path.getctime)
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time.sleep(1)
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image = Image.open(f'../../../output/{os.path.basename(new_file)}')
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buf = io.BytesIO()
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image.save(buf, format='PNG')
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byte_im = buf.getvalue()
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byte_im = base64.b64encode(byte_im).decode('utf-8')
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byte_im = f"data:image/png;base64,{byte_im}"
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print(byte_im)
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return {"byte_im":byte_im}
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if __name__ == "__main__":
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app.run(debug=True)
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@@ -0,0 +1,166 @@
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@keyframes changeprogressbar {
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from{width: 30%;height: 10%;top: 85%;}
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to{width: 40%;height: 5%;top: 80%;}
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}
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@keyframes progressbar {
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0%{left: -5%;}
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50%{left: 100%;}
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100%{left:-5%;}
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}
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@keyframes appearcp {
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from{top: 130%;}
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to{top: 85%;}
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}
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@keyframes appearimg {
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from{top: -30%;}
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to{top: 30%;}
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}
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body{
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background: linear-gradient(to bottom, #3B3486,#332941);
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background-repeat: no-repeat;
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background-attachment: fixed;
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}
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img,canvas{
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box-shadow: 10px 10px 10px black;
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position: absolute;
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left: 50%;
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top: 40%;
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transform: translate(-50%,-50%);
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visibility: hidden;
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}
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#cpcontainer{
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position: fixed;
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background: linear-gradient(to bottom, #F8E559 50%,#e2c90b 100%);
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left: 50%;
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top: 85%;
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transform: translate(-50%,-50%);
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border-radius: 10px;
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width: 30%;
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height: 10%;
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box-shadow: 5px 5px 10px black;
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overflow: hidden;
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animation: appearcp 1s forwards;
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}
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#sticker div{
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font-family: Verdana, Geneva, Tahoma, sans-serif;
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font-size: 150%;
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font-weight: 1000;
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color: #332941;
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position: absolute;
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left: 20%;
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top: 50%;
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}
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#sticker{
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position: absolute;
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top: 50%;
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left: 55%;
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background-color: transparent;
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width: 40%;
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height: 80%;
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cursor: pointer;
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}
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#cpcontainer *{
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top: 50%;
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transform: translate(0,-50%);
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}
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#inputimg{
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position: absolute;
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left: 50%;
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top: 30%;
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transform: translate(-50%,-50%);
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width: 50%;
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height: 50%;
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animation: appearimg 1s forwards;
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}
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#inp{
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opacity: 0;
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width: 100%;
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height: 100%;
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}
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#inplbl{
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position: fixed;
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background: grey;
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left: 50%;
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top: 85%;
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transform: translate(-50%,-50%);
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border-radius: 10px;
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width: 100%;
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height: 100%;
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opacity: 0.25;
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}
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#settings{
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position: absolute;
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top: 50%;
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left: 5%;
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background-color: transparent;
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width: 50%;
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height: 80%;
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}
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.settings{
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position: absolute;
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top: 50%;
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background-color: rgba(128, 128, 128, 0.2);
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width: 20%;
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height: 50%;
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border-radius: 10px;
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cursor: pointer;
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transition: 1s;
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}
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.settings div{
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position: absolute;
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top: 50%;
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left: 40%;
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font-family: Verdana, Geneva, Tahoma, sans-serif;
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font-size: 150%;
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font-weight: 1000;
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color: #332941;
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}
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#setting1{
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left: 5%;
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background-color: rgba(128, 128, 128, 0.4);
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}
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#setting2{
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left: 35%;
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}
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#setting3{
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left: 65%;
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}
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.settings:hover{
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background-color: rgba(128, 128, 128, 0.4);
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}
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#sticker:hover{
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text-shadow: -5px -5px 0 white, 5px -5px 0 white, -5px 5px 0 white, 5px 5px 0 white;
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}
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#progressanimation{
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position: absolute;
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left: -5%;
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top: 50%;
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width: 22%;
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height: 90%;
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background: linear-gradient(to left,transparent,white,transparent);
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opacity: 0.6;
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visibility: hidden;
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}
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@@ -0,0 +1,183 @@
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var image = "";
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var image1 = "";
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var image2 = "";
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var setting = 1;
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var animationflag = false;
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var animationdirection = false;
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function select(evt){
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evt.target.style.background = "rgba(128, 128, 128, 0.4)";
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setting = parseInt(evt.target.id.slice(7));
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console.log(setting);
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for(let i = 0; i<3;i++){
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if(evt.target.id != "setting1"){
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document.getElementById("setting1").style.background = "rgba(128, 128, 128, 0.2)";
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}
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if(evt.target.id != "setting2"){
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document.getElementById("setting2").style.background = "rgba(128, 128, 128, 0.2)";
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}
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if(evt.target.id != "setting3"){
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document.getElementById("setting3").style.background = "rgba(128, 128, 128, 0.2)";
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}
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}
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}
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function changeimg(evt){
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if(image!=""){
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image1 = image;
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}
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document.getElementById("image").style.visibility = "visible";
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document.getElementById("image").style.boxShadow = "10px 10px 10px black";
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document.getElementById("inplbl").style.opacity = "0";
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document.getElementById("image").src = URL.createObjectURL(evt.target.files[0]);
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var img = new Image;
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img.src = URL.createObjectURL(evt.target.files[0]);
|
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img.onload = function(){
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var canvas = document.getElementById("canvas");
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var ctx = canvas.getContext("2d");
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ctx.clearRect(0, 0, canvas.width, canvas.height);
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ctx.drawImage(document.getElementById("image"), 0, 0);
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data = ctx.getImageData(0, 0, canvas.width,canvas.height).data;
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pxls = [];
|
||||
for (let i = 0; i < data.length; i += 4) {
|
||||
var pixel = [];
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pixel.push(data[i]);
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||||
pixel.push(data[i+1]);
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||||
pixel.push(data[i+2]);
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||||
pixel.push(data[i+3]);
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||||
pxls.push(pixel);
|
||||
}
|
||||
var pxlsarray = [[]];
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||||
for(i = 0;i<pxls.length;i++){
|
||||
pxlsarray[pxlsarray.length-1].push(pxls[i]);
|
||||
if(i<pxls.length-2){
|
||||
if((i+1)%canvas.width==0 && i>canvas.width-10){
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||||
pxlsarray.push([]);
|
||||
}
|
||||
}
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||||
|
||||
}
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||||
image = pxlsarray;
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||||
if(image1!=""){
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image2 = image;
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||||
mix();
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
function stickerize(){
|
||||
|
||||
document.getElementById("sticker").style.visibility = "hidden";
|
||||
document.getElementById("settings").style.opacity = "0";
|
||||
document.getElementById("cpcontainer").style.animation = null;
|
||||
document.getElementById("cpcontainer").offsetHeight;
|
||||
document.getElementById("cpcontainer").style.animation = "changeprogressbar 1s forwards";
|
||||
setTimeout(() => {
|
||||
document.getElementById("progressanimation").style.visibility = "visible";
|
||||
document.getElementById("progressanimation").style.animation = null;
|
||||
document.getElementById("progressanimation").offsetHeight;
|
||||
document.getElementById("progressanimation").style.animation = "progressbar 1s infinite";
|
||||
}, 1000);
|
||||
fetch("http://localhost:5000/stickerize",{
|
||||
method: 'POST',
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify({"image":image})
|
||||
}).
|
||||
then(function (response) {
|
||||
return response.json();
|
||||
})
|
||||
.then(data => {
|
||||
document.getElementById("image").src = String(data["byte_im"]);
|
||||
document.getElementById("image").style.boxShadow = "0px 0px 0px transparent";
|
||||
image = "";
|
||||
image1 = "";
|
||||
image2 = "";
|
||||
animationflag = true;
|
||||
document.getElementById("progressanimation").style.visibility = "hidden";
|
||||
document.getElementById("progressanimation").style.animation = null;
|
||||
document.getElementById("progressanimation").offsetHeight;
|
||||
document.getElementById("cpcontainer").style.animation = null;
|
||||
document.getElementById("cpcontainer").offsetHeight;
|
||||
document.getElementById("cpcontainer").style.animation = "changeprogressbar 1s reverse";
|
||||
setTimeout(() => {
|
||||
document.getElementById("settings").style.opacity = "1";
|
||||
document.getElementById("sticker").style.visibility = "visible";
|
||||
animationflag = false;
|
||||
}, 1000);
|
||||
})
|
||||
|
||||
}
|
||||
|
||||
function mix(){
|
||||
|
||||
document.getElementById("sticker").style.visibility = "hidden";
|
||||
document.getElementById("settings").style.opacity = "0";
|
||||
document.getElementById("cpcontainer").style.animation = null;
|
||||
document.getElementById("cpcontainer").offsetHeight;
|
||||
document.getElementById("cpcontainer").style.animation = "changeprogressbar 1s forwards";
|
||||
setTimeout(() => {
|
||||
document.getElementById("progressanimation").style.visibility = "visible";
|
||||
document.getElementById("progressanimation").style.animation = null;
|
||||
document.getElementById("progressanimation").offsetHeight;
|
||||
document.getElementById("progressanimation").style.animation = "progressbar 1s infinite";
|
||||
}, 1000);
|
||||
fetch("http://localhost:5000/mix",{
|
||||
method: 'POST',
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify({"image1":image1,"image2":image2,"setting":setting})
|
||||
}).
|
||||
then(function (response) {
|
||||
return response.json();
|
||||
})
|
||||
.then(data => {
|
||||
document.getElementById("image").src = String(data["byte_im"]);
|
||||
var img = new Image;
|
||||
img.src = document.getElementById("image").src;
|
||||
img.onload = function(){
|
||||
var canvas = document.getElementById("canvas");
|
||||
var ctx = canvas.getContext("2d");
|
||||
ctx.clearRect(0, 0, canvas.width, canvas.height);
|
||||
ctx.drawImage(document.getElementById("image"), 0, 0);
|
||||
data = ctx.getImageData(0, 0, canvas.width,canvas.height).data;
|
||||
pxls = [];
|
||||
for (let i = 0; i < data.length; i += 4) {
|
||||
var pixel = [];
|
||||
pixel.push(data[i]);
|
||||
pixel.push(data[i+1]);
|
||||
pixel.push(data[i+2]);
|
||||
pixel.push(data[i+3]);
|
||||
pxls.push(pixel);
|
||||
}
|
||||
var pxlsarray = [[]];
|
||||
for(i = 0;i<pxls.length;i++){
|
||||
pxlsarray[pxlsarray.length-1].push(pxls[i]);
|
||||
if(i<pxls.length-2){
|
||||
if((i+1)%canvas.width==0 && i>canvas.width-10){
|
||||
pxlsarray.push([]);
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
image = pxlsarray;
|
||||
}
|
||||
image1 = "";
|
||||
image2 = "";
|
||||
animationflag = true;
|
||||
document.getElementById("progressanimation").style.visibility = "hidden";
|
||||
document.getElementById("progressanimation").style.animation = null;
|
||||
document.getElementById("progressanimation").offsetHeight;
|
||||
document.getElementById("cpcontainer").style.animation = null;
|
||||
document.getElementById("cpcontainer").offsetHeight;
|
||||
document.getElementById("cpcontainer").style.animation = "changeprogressbar 1s reverse";
|
||||
setTimeout(() => {
|
||||
document.getElementById("settings").style.opacity = "1";
|
||||
document.getElementById("sticker").style.visibility = "visible";
|
||||
animationflag = false;
|
||||
}, 1000);
|
||||
})
|
||||
|
||||
}
|
||||
@@ -0,0 +1,699 @@
|
||||
{
|
||||
"1": {
|
||||
"inputs": {
|
||||
"seed": 0,
|
||||
"prompt": "",
|
||||
"negative_prompt": "",
|
||||
"steps": 4,
|
||||
"width": 512,
|
||||
"height": 512,
|
||||
"cfg": 1.5,
|
||||
"style_fidelity": 0.5,
|
||||
"strength": 1,
|
||||
"batch": 1,
|
||||
"ipadapter_scale": 0.6,
|
||||
"controlnet_conditioning_scale": 0.6,
|
||||
"reference_only": "enable",
|
||||
"ip_adapter": "enable",
|
||||
"control_net": "enable",
|
||||
"pipe": [
|
||||
"2",
|
||||
0
|
||||
],
|
||||
"image": [
|
||||
"22",
|
||||
0
|
||||
],
|
||||
"control_image": [
|
||||
"79",
|
||||
0
|
||||
],
|
||||
"reference_image": [
|
||||
"22",
|
||||
0
|
||||
],
|
||||
"ipadapter_image": [
|
||||
"22",
|
||||
1
|
||||
]
|
||||
},
|
||||
"class_type": "LCMLora_ipadapter"
|
||||
},
|
||||
"2": {
|
||||
"inputs": {
|
||||
"device": "GPU",
|
||||
"tomesd_value": 0.6,
|
||||
"ip_adapter_model": "ip-adapter_sd15.bin",
|
||||
"reference_only": "enable",
|
||||
"ip_adapter": "enable",
|
||||
"control_net": "enable",
|
||||
"model_name": "Juggernaut",
|
||||
"controlnet_model": "cn_depth"
|
||||
},
|
||||
"class_type": "LCMLoraLoader_ipadapter"
|
||||
},
|
||||
"5": {
|
||||
"inputs": {
|
||||
"low_threshold": 100,
|
||||
"high_threshold": 200,
|
||||
"resolution": 512
|
||||
},
|
||||
"class_type": "CannyEdgePreprocessor"
|
||||
},
|
||||
"7": {
|
||||
"inputs": {
|
||||
"seed": 0,
|
||||
"prompt": "",
|
||||
"negative_prompt": "",
|
||||
"steps": 4,
|
||||
"width": 512,
|
||||
"height": 512,
|
||||
"cfg": 1.5,
|
||||
"style_fidelity": 0.5,
|
||||
"strength": 1,
|
||||
"batch": 1,
|
||||
"ipadapter_scale": 0.6,
|
||||
"controlnet_conditioning_scale": 0.6,
|
||||
"reference_only": "enable",
|
||||
"ip_adapter": "enable",
|
||||
"control_net": "enable",
|
||||
"pipe": [
|
||||
"2",
|
||||
0
|
||||
],
|
||||
"image": [
|
||||
"22",
|
||||
1
|
||||
],
|
||||
"control_image": [
|
||||
"80",
|
||||
0
|
||||
],
|
||||
"reference_image": [
|
||||
"22",
|
||||
1
|
||||
],
|
||||
"ipadapter_image": [
|
||||
"13",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "LCMLora_ipadapter"
|
||||
},
|
||||
"11": {
|
||||
"inputs": {
|
||||
"low_threshold": 100,
|
||||
"high_threshold": 200,
|
||||
"resolution": 512
|
||||
},
|
||||
"class_type": "CannyEdgePreprocessor"
|
||||
},
|
||||
"13": {
|
||||
"inputs": {
|
||||
"image": [
|
||||
"1",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "ImageOutputToComfyNodes"
|
||||
},
|
||||
"18": {
|
||||
"inputs": {
|
||||
"stitch": "right",
|
||||
"feathering": 0,
|
||||
"image_a": [
|
||||
"22",
|
||||
0
|
||||
],
|
||||
"image_b": [
|
||||
"22",
|
||||
1
|
||||
]
|
||||
},
|
||||
"class_type": "Image Stitch"
|
||||
},
|
||||
"19": {
|
||||
"inputs": {
|
||||
"stitch": "bottom",
|
||||
"feathering": 0,
|
||||
"image_a": [
|
||||
"18",
|
||||
0
|
||||
],
|
||||
"image_b": [
|
||||
"20",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "Image Stitch"
|
||||
},
|
||||
"20": {
|
||||
"inputs": {
|
||||
"stitch": "right",
|
||||
"feathering": 0,
|
||||
"image_a": [
|
||||
"13",
|
||||
0
|
||||
],
|
||||
"image_b": [
|
||||
"21",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "Image Stitch"
|
||||
},
|
||||
"21": {
|
||||
"inputs": {
|
||||
"image": [
|
||||
"7",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "ImageOutputToComfyNodes"
|
||||
},
|
||||
"22": {
|
||||
"inputs": {
|
||||
"switch": "disable",
|
||||
"image_1": [
|
||||
"169",
|
||||
0
|
||||
],
|
||||
"image_2": [
|
||||
"170",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "ImageSwitch"
|
||||
},
|
||||
"23": {
|
||||
"inputs": {
|
||||
"sf_1": 0.6,
|
||||
"sf_2": 0.6,
|
||||
"sf_3": 0.6,
|
||||
"strength_1": 0.6,
|
||||
"strength_2": 0.6,
|
||||
"strength_3": 0.6,
|
||||
"IPAScale_1": 0.6,
|
||||
"IPAScale_2": 0.6,
|
||||
"IPAScale_3": 0.6,
|
||||
"CNScale_1": 0.6,
|
||||
"CNScale_2": 0.6,
|
||||
"CNScale_3": 0.6,
|
||||
"setting": "v3"
|
||||
},
|
||||
"class_type": "SettingsSwitch"
|
||||
},
|
||||
"26": {
|
||||
"inputs": {
|
||||
"Number": 0.8
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"27": {
|
||||
"inputs": {
|
||||
"Number": 0.8200000000000001
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"28": {
|
||||
"inputs": {
|
||||
"Number": 0.3
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"29": {
|
||||
"inputs": {
|
||||
"Number": 0.7000000000000001
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"30": {
|
||||
"inputs": {
|
||||
"Number": 0.25
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"31": {
|
||||
"inputs": {
|
||||
"Number": 0.05
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"32": {
|
||||
"inputs": {
|
||||
"Number": 0.07
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"33": {
|
||||
"inputs": {
|
||||
"Number": 0.08
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"34": {
|
||||
"inputs": {
|
||||
"Number": 0.55
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"35": {
|
||||
"inputs": {
|
||||
"Number": 0.1
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"36": {
|
||||
"inputs": {
|
||||
"Number": 0.65
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"37": {
|
||||
"inputs": {
|
||||
"Number": 0.9
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"38": {
|
||||
"inputs": {
|
||||
"sf_1": 0.6,
|
||||
"sf_2": 0.6,
|
||||
"sf_3": 0.6,
|
||||
"strength_1": 0.6,
|
||||
"strength_2": 0.6,
|
||||
"strength_3": 0.6,
|
||||
"IPAScale_1": 0.6,
|
||||
"IPAScale_2": 0.6,
|
||||
"IPAScale_3": 0.6,
|
||||
"CNScale_1": 0.6,
|
||||
"CNScale_2": 0.6,
|
||||
"CNScale_3": 0.6,
|
||||
"setting": "v1"
|
||||
},
|
||||
"class_type": "SettingsSwitch"
|
||||
},
|
||||
"39": {
|
||||
"inputs": {
|
||||
"Number": 0.73
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"40": {
|
||||
"inputs": {
|
||||
"Number": 0.2
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"41": {
|
||||
"inputs": {
|
||||
"Number": 0.85
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"42": {
|
||||
"inputs": {
|
||||
"Number": 0.72
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"43": {
|
||||
"inputs": {
|
||||
"Number": 0.88
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"44": {
|
||||
"inputs": {
|
||||
"Number": 0.1
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"45": {
|
||||
"inputs": {
|
||||
"Number": 0.09
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"46": {
|
||||
"inputs": {
|
||||
"Number": 0.85
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"47": {
|
||||
"inputs": {
|
||||
"sf_1": 0.6,
|
||||
"sf_2": 0.6,
|
||||
"sf_3": 0.6,
|
||||
"strength_1": 0.6,
|
||||
"strength_2": 0.6,
|
||||
"strength_3": 0.6,
|
||||
"IPAScale_1": 0.6,
|
||||
"IPAScale_2": 0.6,
|
||||
"IPAScale_3": 0.6,
|
||||
"CNScale_1": 0.6,
|
||||
"CNScale_2": 0.6,
|
||||
"CNScale_3": 0.6,
|
||||
"setting": "v3"
|
||||
},
|
||||
"class_type": "SettingsSwitch"
|
||||
},
|
||||
"48": {
|
||||
"inputs": {
|
||||
"Number": 0.45
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"49": {
|
||||
"inputs": {
|
||||
"Number": 0.8200000000000001
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"50": {
|
||||
"inputs": {
|
||||
"Number": 0.96
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"51": {
|
||||
"inputs": {
|
||||
"Number": 0.04
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"59": {
|
||||
"inputs": {
|
||||
"Number": 0.99
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"60": {
|
||||
"inputs": {
|
||||
"Number": 0.75
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"61": {
|
||||
"inputs": {
|
||||
"Number": 0.8
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"62": {
|
||||
"inputs": {
|
||||
"Number": 0.5
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"64": {
|
||||
"inputs": {
|
||||
"Number": 0.06
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"76": {
|
||||
"inputs": {
|
||||
"a": 6.28,
|
||||
"bg_threshold": 0.1,
|
||||
"resolution": 512
|
||||
},
|
||||
"class_type": "MiDaS-DepthMapPreprocessor"
|
||||
},
|
||||
"77": {
|
||||
"inputs": {
|
||||
"a": 6.28,
|
||||
"bg_threshold": 0.1,
|
||||
"resolution": 512
|
||||
},
|
||||
"class_type": "MiDaS-DepthMapPreprocessor"
|
||||
},
|
||||
"79": {
|
||||
"inputs": {
|
||||
"rm_nearest": 0,
|
||||
"rm_background": 0,
|
||||
"boost": "disable",
|
||||
"resolution": 512,
|
||||
"image": [
|
||||
"22",
|
||||
0
|
||||
]
|
||||
},
|
||||
"class_type": "LeReS-DepthMapPreprocessor"
|
||||
},
|
||||
"80": {
|
||||
"inputs": {
|
||||
"rm_nearest": 0,
|
||||
"rm_background": 0,
|
||||
"boost": "disable",
|
||||
"resolution": 512,
|
||||
"image": [
|
||||
"22",
|
||||
1
|
||||
]
|
||||
},
|
||||
"class_type": "LeReS-DepthMapPreprocessor"
|
||||
},
|
||||
"81": {
|
||||
"inputs": {
|
||||
"Number": 0.8
|
||||
},
|
||||
"class_type": "FloatNumber"
|
||||
},
|
||||
"83": {
|
||||
"inputs": {
|
||||
"seed": 0,
|
||||
"prompt": "",
|
||||
"negative_prompt": "",
|
||||
"steps": 2,
|
||||
"width": 512,
|
||||
"height": 512,
|
||||
"cfg": 1.5,
|
||||
"style_fidelity": 0.5,
|
||||
"strength": 1,
|
||||
"batch": 1,
|
||||
"ipadapter_scale": 0.6,
|
||||
"controlnet_conditioning_scale": 0.6,
|
||||
"reference_only": "enable",
|
||||
"ip_adapter": "enable",
|
||||
"control_net": "enable",
|
||||
"pipe": [
|
||||
"2",
|
||||
0
|
||||
],
|
||||
"image": [
|
||||
"84",
|
||||
0
|
||||
],
|
||||
"control_image": [
|
||||
"85",
|
||||
0
|
||||
],
|
||||
"reference_image": [
|
||||
"84",
|
||||
0
|
||||
],
|
||||
"ipadapter_image": [
|
||||
"22",
|
||||
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@@ -0,0 +1,32 @@
|
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<!DOCTYPE html>
|
||||
<html>
|
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<head>
|
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<link rel="stylesheet" href="/static/mix.css">
|
||||
</head>
|
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<body>
|
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
||||
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|
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<div>1</div>
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
</div>
|
||||
<div id="sticker" onclick="stickerize();">
|
||||
<div>STICKERIZE</div>
|
||||
</div>
|
||||
<div id="progressanimation"></div>
|
||||
</div>
|
||||
</body>
|
||||
</html>
|
||||
Reference in New Issue
Block a user