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Update app.py
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app.py
CHANGED
@@ -3,7 +3,7 @@ from PIL import Image
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import os
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import tempfile
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import pyheif
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def open_heic_image(image_path):
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heif_file = pyheif.read(image_path)
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@@ -18,6 +18,10 @@ def open_heic_image(image_path):
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return img
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def optimize_image(image, png_optimize, jpeg_quality, jpeg_resolution, webp_quality):
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# Manejar archivos HEIC
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if image.name.lower().endswith(".heic"):
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img = open_heic_image(image.name)
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@@ -32,51 +36,50 @@ def optimize_image(image, png_optimize, jpeg_quality, jpeg_resolution, webp_qual
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output_dir = "/tmp/optimized_images"
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os.makedirs(output_dir, exist_ok=True)
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results = []
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# Optimización para PNG
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if png_optimize:
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lossless_output_path = os.path.join(output_dir, "lossless.png")
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img.save(lossless_output_path, format="PNG", optimize=True)
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lossless_size = os.path.getsize(lossless_output_path) / 1024
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# Optimización para JPEG
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lossy_output_path = os.path.join(output_dir, "lossy.jpg")
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img.save(lossy_output_path, format="JPEG", quality=jpeg_quality, optimize=True)
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lossy_size = os.path.getsize(lossy_output_path) / 1024
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# Reducción de resolución (JPEG)
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reduced_output_path = os.path.join(output_dir, "reduced_resolution.jpg")
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new_resolution = (img.width * jpeg_resolution // 100, img.height * jpeg_resolution // 100)
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reduced_img = img.resize(new_resolution, Image.LANCZOS)
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reduced_img.save(reduced_output_path, format="JPEG", quality=jpeg_quality, optimize=True)
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reduced_size = os.path.getsize(reduced_output_path) / 1024
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# Optimización para WebP
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webp_lossy_output_path = os.path.join(output_dir, "lossy.webp")
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img.save(webp_lossy_output_path, format="WEBP", quality=webp_quality, optimize=True)
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webp_lossy_size = os.path.getsize(webp_lossy_output_path) / 1024
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#
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outputs = []
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for
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img = Image.open(path)
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percent_reduction = 100 * (original_size - size) / original_size
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outputs.extend([img, f"{format_name}: {size:.2f} KB\n(diferencia: {-percent_reduction:.2f} KB)", path])
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else:
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outputs.extend([None, "", None])
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return outputs
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def apply_model(image, model_name):
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model_pipeline = pipeline("image-super-resolution", model=model_name)
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return model_pipeline(image)
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with gr.Blocks() as demo:
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with gr.Tab("Optimización Tradicional"):
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@@ -92,19 +95,19 @@ with gr.Blocks() as demo:
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with gr.Column():
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optimized_output2 = gr.Image(label="Optimización con pérdida (JPEG)")
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jpeg_quality = gr.Slider(label="Calidad JPEG", minimum=10, maximum=100, value=
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download_button2 = gr.File(label="Descargar", visible=True)
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optimized_size2 = gr.Text(value="", interactive=False, show_label=False)
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with gr.Column():
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optimized_output3 = gr.Image(label="Reducción de resolución (JPEG)")
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jpeg_resolution = gr.Slider(label="Resolución JPEG (%)", minimum=10, maximum=100, value=
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download_button3 = gr.File(label="Descargar", visible=True)
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optimized_size3 = gr.Text(value="", interactive=False, show_label=False)
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with gr.Column():
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optimized_output4 = gr.Image(label="Optimización WebP con pérdida")
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webp_quality = gr.Slider(label="Calidad WebP", minimum=10, maximum=100, value=
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download_button4 = gr.File(label="Descargar", visible=True)
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optimized_size4 = gr.Text(value="", interactive=False, show_label=False)
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@@ -120,20 +123,4 @@ with gr.Blocks() as demo:
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]
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)
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with gr.Tab("Optimización con Modelos de Hugging Face"):
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hf_image_input = gr.File(label="Sube tu imagen para optimización avanzada", file_types=['image', '.heic'])
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model_selector = gr.Dropdown(
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label="Selecciona un modelo",
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choices=["xinntao/Real-ESRGAN", "google/ddpm-cifar10-32", "facebook/ddpm"], # Añade los modelos disponibles
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value="xinntao/Real-ESRGAN"
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)
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hf_output = gr.Image(label="Resultado")
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hf_button = gr.Button("Aplicar Modelo")
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hf_button.click(
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fn=apply_model,
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inputs=[hf_image_input, model_selector],
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outputs=hf_output
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)
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demo.launch()
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import os
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import tempfile
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import pyheif
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import ntpath
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def open_heic_image(image_path):
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heif_file = pyheif.read(image_path)
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return img
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def optimize_image(image, png_optimize, jpeg_quality, jpeg_resolution, webp_quality):
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# Obtener el nombre del archivo original sin la extensión
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original_filename = ntpath.basename(image.name)
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base_name, ext = os.path.splitext(original_filename)
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# Manejar archivos HEIC
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if image.name.lower().endswith(".heic"):
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img = open_heic_image(image.name)
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output_dir = "/tmp/optimized_images"
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os.makedirs(output_dir, exist_ok=True)
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# Lista para almacenar los resultados
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results = []
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# Optimización para PNG
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if png_optimize:
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lossless_output_path = os.path.join(output_dir, f"{base_name}-lossless.png")
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img.save(lossless_output_path, format="PNG", optimize=True)
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lossless_size = os.path.getsize(lossless_output_path) / 1024
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percent_reduction = 100 * (original_size - lossless_size) / original_size
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results.append((Image.open(lossless_output_path), f"PNG: {lossless_size:.2f} KB (diferencia: {-percent_reduction:.2f} KB)", lossless_output_path))
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# Optimización para JPEG
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lossy_output_path = os.path.join(output_dir, f"{base_name}-lossy.jpg")
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img.save(lossy_output_path, format="JPEG", quality=jpeg_quality, optimize=True)
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lossy_size = os.path.getsize(lossy_output_path) / 1024
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percent_reduction = 100 * (original_size - lossy_size) / original_size
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results.append((Image.open(lossy_output_path), f"JPEG: {lossy_size:.2f} KB (diferencia: {-percent_reduction:.2f} KB)", lossy_output_path))
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# Reducción de resolución (JPEG)
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reduced_output_path = os.path.join(output_dir, f"{base_name}-reduced_resolution.jpg")
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new_resolution = (img.width * jpeg_resolution // 100, img.height * jpeg_resolution // 100)
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reduced_img = img.resize(new_resolution, Image.LANCZOS)
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reduced_img.save(reduced_output_path, format="JPEG", quality=jpeg_quality, optimize=True)
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reduced_size = os.path.getsize(reduced_output_path) / 1024
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percent_reduction = 100 * (original_size - reduced_size) / original_size
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results.append((Image.open(reduced_output_path), f"JPEG (resolución reducida): {reduced_size:.2f} KB (diferencia: {-percent_reduction:.2f} KB)", reduced_output_path))
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# Optimización para WebP
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webp_lossy_output_path = os.path.join(output_dir, f"{base_name}-lossy.webp")
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img.save(webp_lossy_output_path, format="WEBP", quality=webp_quality, optimize=True)
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webp_lossy_size = os.path.getsize(webp_lossy_output_path) / 1024
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percent_reduction = 100 * (original_size - webp_lossy_size) / original_size
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results.append((Image.open(webp_lossy_output_path), f"WebP: {webp_lossy_size:.2f} KB (diferencia: {-percent_reduction:.2f} KB)", webp_lossy_output_path))
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# Asegurarse de que todos los resultados están presentes (4 entradas)
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while len(results) < 4:
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results.append((None, "", None))
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# Dividir los resultados en imágenes, textos y rutas para descarga
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outputs = []
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for result in results:
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outputs.extend(result)
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return outputs
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with gr.Blocks() as demo:
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with gr.Tab("Optimización Tradicional"):
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with gr.Column():
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optimized_output2 = gr.Image(label="Optimización con pérdida (JPEG)")
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jpeg_quality = gr.Slider(label="Calidad JPEG", minimum=10, maximum=100, value=75, step=1)
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download_button2 = gr.File(label="Descargar", visible=True)
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optimized_size2 = gr.Text(value="", interactive=False, show_label=False)
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with gr.Column():
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optimized_output3 = gr.Image(label="Reducción de resolución (JPEG)")
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jpeg_resolution = gr.Slider(label="Resolución JPEG (%)", minimum=10, maximum=100, value=75, step=1)
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download_button3 = gr.File(label="Descargar", visible=True)
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optimized_size3 = gr.Text(value="", interactive=False, show_label=False)
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with gr.Column():
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optimized_output4 = gr.Image(label="Optimización WebP con pérdida")
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webp_quality = gr.Slider(label="Calidad WebP", minimum=10, maximum=100, value=75, step=1)
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download_button4 = gr.File(label="Descargar", visible=True)
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optimized_size4 = gr.Text(value="", interactive=False, show_label=False)
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]
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)
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demo.launch()
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