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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() |