Datasets:
File size: 3,785 Bytes
5bbe62a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 | import io
import base64
import json
from PIL import Image
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import uvicorn
import cv2
import numpy as np
import sys
sys.setrecursionlimit(64*64)
def extract_skin(img):
# as rgba
mask = Image.open('skin-mask.png')
img = img.convert('RGBA')
# crop to half size
img = img.crop((0, 0, img.width // 2, img.height // 2))
bg_color = img.getpixel((0, 0))
def color_diff(a,b):
return 0.299*(a[0]-b[0])**2 + 0.587*(a[1]-b[1])**2 + 0.114*(a[2]-b[2])**2
dot_color = (255,255,255)
ratio = img.width // 64
ignore_map = {}
t1 = 3000
t2 = 2000
for x in range(64):
for y in range(64):
if mask.getpixel((x, y))[3] == 0:
if (color_diff(img.getpixel((x*ratio+2, y*ratio+2)), dot_color) < t1 or\
color_diff(img.getpixel((x*ratio+2, y*ratio+3)), dot_color) < t1 or\
color_diff(img.getpixel((x*ratio+3, y*ratio+3)), dot_color) < t1 or\
color_diff(img.getpixel((x*ratio+3, y*ratio+2)), dot_color) < t1) and\
(color_diff(img.getpixel((x*ratio+1, y*ratio+1)), bg_color) < t2 or\
color_diff(img.getpixel((x*ratio+4, y*ratio+4)), bg_color) <t2 or\
color_diff(img.getpixel((x*ratio+1, y*ratio+4)), bg_color) < t2 or\
color_diff(img.getpixel((x*ratio+4, y*ratio+1)), bg_color) < t2):
ignore_map[(x, y)] = True
else:
# Set 6x6 area to the color of the central 4x4 pixels
c= img.getpixel((x*ratio+2, y*ratio+2))
for i in range(x*ratio, x*ratio+6):
for j in range(y*ratio, y*ratio+6):
img.putpixel((i, j),c)
img = img.resize((64, 64), Image.BOX)
for x in range(64):
for y in range(64):
if ignore_map.get((x, y), False):
img.putpixel((x,y),(0,0,0,0))
img.save('test_tmp.png')
return img
class ExtractSkinRequest(BaseModel):
img: str
if __name__ == '__main__':
# from args
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--img', type=str, default="test_1.png")
parser.add_argument('--output', type=str, default="test_output.png")
parser.add_argument('--server', type=str, default='False')
args = parser.parse_args()
if args.server.lower() == 'false':
img = Image.open(args.img)
res_img = extract_skin(img)
res_img.save(args.output)
else:
# start server
app = FastAPI()
# Configure CORS
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
#listen 10010
@app.post('/extract')
def extract(request: ExtractSkinRequest):
try:
# from request json body img:base64
img_data = base64.b64decode(request.img)
img = Image.open(io.BytesIO(img_data))
# response json {img:base64}
res_img = extract_skin(img)
# Convert PIL Image to base64 PNG
buffered = io.BytesIO()
res_img.save(buffered, format="PNG")
res_img.save('tmp.png')
img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
return {'img': img_str}
except Exception as e:
raise HTTPException(status_code=400, detail=str(e))
uvicorn.run(app, host="0.0.0.0", port=10010) |