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import os
os.environ["NUMBA_CACHE_DIR"] = "/tmp/numba_cache"
os.environ["U2NET_HOME"] = "/tmp/u2net"
from fastapi import FastAPI, HTTPException
from fastapi.responses import StreamingResponse
import requests
from io import BytesIO
from PIL import Image, ImageFilter, ImageEnhance
import rembg
import onnxruntime as ort
app = FastAPI()
# Limita o número de threads do onnxruntime
options = ort.SessionOptions()
options.intra_op_num_threads = 2
def resize_image(image, max_size=1024):
width, height = image.size
if width > max_size or height > max_size:
ratio = min(max_size / width, max_size / height)
new_size = (int(width * ratio), int(height * ratio))
image = image.resize(new_size, Image.Resampling.LANCZOS) # Usando LANCZOS em vez de ANTIALIAS
return image
def adjust_brightness_contrast(image, brightness=1.2, contrast=1.2):
enhancer = ImageEnhance.Brightness(image)
image = enhancer.enhance(brightness)
enhancer = ImageEnhance.Contrast(image)
image = enhancer.enhance(contrast)
return image
@app.get("/remove-background")
async def remove_background(image_url: str):
try:
# Baixa a imagem da URL fornecida
response = requests.get(image_url)
response.raise_for_status()
# Abre a imagem usando Pillow
image = Image.open(BytesIO(response.content))
# Pré-processamento: redimensiona e ajusta brilho/contraste
image = resize_image(image, max_size=1024)
image = adjust_brightness_contrast(image)
# Remove o fundo da imagem usando rembg
output = rembg.remove(image, model="u2net", session_options=options)
# Pós-processamento: suaviza as bordas
output = output.filter(ImageFilter.SMOOTH_MORE)
# Converte a imagem de volta para bytes
img_byte_arr = BytesIO()
output.save(img_byte_arr, format='PNG')
img_byte_arr.seek(0)
# Retorna a imagem processada diretamente no navegador
return StreamingResponse(img_byte_arr, media_type="image/png")
except Exception as e:
raise HTTPException(status_code=400, detail=str(e)) |