ok denovo

download_models.py

@@ -1,7 +1,7 @@
 import os
 import sys
 from huggingface_hub import snapshot_download
-from backgroundremover.bg import remove
+from transparent_background import Remover
 from PIL import Image
 
 #1. Baixa o modelo ConvNext
@@ -14,7 +14,8 @@ print("Downloading backgroundremover model (u2net)...")
 #Usa o truque da imagem falsa de 1x1 para forçar o download
 img = Image.new('RGB', (1, 1), 'black')
 try:
-    remove(img)
+    remover = Remover()
+    remover.process(img)
 except Exception as e:
     # A execução vai falhar na imagem 1x1, o que é esperado.
     # Nós não nos importamos, contanto que o download tenha sido disparado.

feature_extractor_single.py

@@ -2,7 +2,7 @@ import os
 import torch
 import numpy as np
 from PIL import Image
-from backgroundremover.bg import remove
+from transparent_background import Remover
 from torchvision import transforms
 from transformers import ConvNextImageProcessor, ConvNextForImageClassification
 
@@ -17,7 +17,8 @@ def segment_and_whitebg(image_path: str, save_dir: str = "processed") -> str:
 
     #Remove fundo
     input_img = Image.open(image_path).convert("RGB")
-    output = remove(input_img)
+    remover = Remover() #Inicializa o modelo
+    output = remover.process(input_img, type='rgba') #Processa e retorna PIL
 
     #Adiciona fundo branco
     bg = Image.new("RGBA", output.size, (255, 255, 255, 255))

main.py

@@ -1,7 +1,4 @@
-#Desabilita o cache do Numba ANTES que qualquer outra
-#biblioteca (fastapi, feature_extractor, etc.) seja importada.
 import os
-os.environ["NUMBA_DISABLE_CACHING"] = "1"
 import shutil
 from fastapi import FastAPI, File, UploadFile, Depends, HTTPException, status
 from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials

requirements.txt

@@ -19,7 +19,7 @@ timm==0.9.16
 # Processamento de imagem
 # =====================================
 pillow==10.3.0
-backgroundremover==0.3.5
+transparent-background==1.3.4
 onnxruntime==1.19.2
 numpy==1.26.4