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import gradio as gr
import cv2
import os
import random
import zipfile
from PIL import Image
from datetime import datetime
def procesar_video(video_path):
try:
# Configurar directorio temporal
temp_dir = f"temp_{datetime.now().strftime('%Y%m%d%H%M%S')}"
os.makedirs(temp_dir, exist_ok=True)
# Leer el video y extraer TODOS los frames
cap = cv2.VideoCapture(video_path)
frame_count = 0
frame_paths = []
while True:
ret, frame = cap.read()
if not ret:
break
# Guardar cada frame
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
img = Image.fromarray(frame_rgb)
img_path = os.path.join(temp_dir, f"frame_{frame_count:04d}.jpg")
img.save(img_path)
frame_paths.append(img_path)
frame_count += 1
cap.release()
if frame_count == 0:
raise ValueError("No se pudieron extraer frames del video")
# Seleccionar 4 frames aleatorios para el collage
selected_frames = random.sample(frame_paths, min(4, len(frame_paths)))
# Crear collage
images = [Image.open(img) for img in selected_frames]
collage = Image.new('RGB', (images[0].width * 2, images[0].height * 2))
for i, img in enumerate(images):
row = i // 2
col = i % 2
x = col * images[0].width
y = row * images[0].height
collage.paste(img, (x, y))
collage_path = os.path.join(temp_dir, "collage.jpg")
collage.save(collage_path)
# Crear archivo ZIP con TODOS los frames
zip_path = os.path.join(temp_dir, "frames.zip")
with zipfile.ZipFile(zip_path, 'w') as zipf:
for img in frame_paths:
zipf.write(img, os.path.basename(img))
return collage_path, zip_path, temp_dir
except Exception as e:
raise gr.Error(f"Error al procesar el video: {str(e)}")
def limpiar_cache(temp_dir):
if temp_dir and os.path.exists(temp_dir):
for file in os.listdir(temp_dir):
os.remove(os.path.join(temp_dir, file))
os.rmdir(temp_dir)
with gr.Blocks(title="Extracci贸n de Fotogramas Forenses") as demo:
gr.Markdown("# Herramienta de Extracci贸n de Fotogramas Forenses")
gr.Markdown("**Carga un video para extraer TODOS los fotogramas y generar un collage de muestra.**")
gr.Markdown("Desarrollado por Jos茅 R. Leonett para el Grupo de Peritos Forenses Digitales de Guatemala - [www.forensedigital.gt](https://www.forensedigital.gt)")
with gr.Row():
with gr.Column():
video_input = gr.Video(label="Subir Video", interactive=True)
procesar_btn = gr.Button("Procesar Fotogramas", interactive=False)
with gr.Column():
gallery_output = gr.Image(label="Collage de Muestra")
download_btn = gr.Button("DESCARGAR FOTOGRAMAS", interactive=False)
download_file = gr.File(label="Archivo ZIP generado", visible=False)
temp_dir_state = gr.State()
def habilitar_procesar(video):
return gr.Button(interactive=True) if video else gr.Button(interactive=False)
def procesar_y_mostrar(video):
limpiar_cache(temp_dir_state.value)
collage_path, zip_path, temp_dir = procesar_video(video)
return collage_path, zip_path, temp_dir, gr.Button(interactive=True)
video_input.change(
fn=habilitar_procesar,
inputs=video_input,
outputs=procesar_btn,
queue=False
)
procesar_btn.click(
fn=procesar_y_mostrar,
inputs=video_input,
outputs=[gallery_output, download_file, temp_dir_state, download_btn],
)
download_btn.click(
fn=lambda temp_dir: os.path.join(temp_dir, "frames.zip"),
inputs=temp_dir_state,
outputs=download_file,
)
if __name__ == "__main__":
demo.launch() |