Upload app (1).py

app (1).py

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+
+import gradio as gr
+import os
+import shutil
+import subprocess
+from PIL import Image
+
+# === Descarga y configuración de Roop ===
+if not os.path.exists("roop"):
+    subprocess.run(["git", "clone", "https://github.com/s0md3v/roop.git"])
+    os.chdir("roop")
+
+    subprocess.run(["pip", "uninstall", "-y", "jax", "jaxlib", "numpy", "tensorflow"])
+    subprocess.run(["pip", "install", "numpy==1.23.5", "jax==0.4.13", "jaxlib==0.4.13", "tensorflow==2.12.0"])
+    subprocess.run(["pip", "install", "-r", "requirements.txt"])
+    
+    os.chdir("..")
+
+def procesar_lote(img_rostro, imgs_objetivo):
+    input_dir = "roop/batch_input"
+    output_dir = "roop/batch_output"
+    
+    shutil.rmtree(input_dir, ignore_errors=True)
+    shutil.rmtree(output_dir, ignore_errors=True)
+    os.makedirs(input_dir, exist_ok=True)
+    os.makedirs(output_dir, exist_ok=True)
+
+    rostro_path = os.path.join("roop", "RB.jpg")
+    img_rostro.save(rostro_path)
+
+    for img_file in imgs_objetivo:
+        image = Image.open(img_file)
+        image.save(os.path.join(input_dir, os.path.basename(img_file)))
+
+    comando = [
+        "python", "roop/run.py",
+        "--source_face", rostro_path,
+        "--target_folder", input_dir,
+        "--output_folder", output_dir,
+        "--frame-processor", "face_swapper"
+    ]
+    subprocess.run(comando)
+
+    zip_path = "roop/resultado.zip"
+    shutil.make_archive(zip_path.replace(".zip", ""), 'zip', output_dir)
+    
+    return zip_path
+
+gr.Interface(
+    fn=procesar_lote,
+    inputs=[
+        gr.Image(label="Rostro base (RB.jpg)", type="pil"),
+        gr.File(file_types=["image"], label="Imágenes a procesar", file_count="multiple")
+    ],
+    outputs=gr.File(label="Descargar resultados ZIP"),
+    title="Intercambio de rostros por lote con Roop",
+    description="Sube una imagen de rostro base y varias imágenes objetivo. El sistema procesará todas y devolverá un ZIP con los resultados.",
+).launch()