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app.py

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+import gradio as gr
+import spaces
+from gradio_imageslider import ImageSlider
+from image_gen_aux import UpscaleWithModel
+from image_gen_aux.utils import load_image
+import tempfile
+from PIL import Image
+import traceback
+import torch
+
+# --- Model Dictionary ---
+# A complete dictionary of your self-trained models.
+MODELS = {
+    "1xDeH264_realplksr": "Phips/1xDeH264_realplksr",
+    "1xDeJPG_HAT": "Phips/1xDeJPG_HAT",
+    "1xDeJPG_OmniSR": "Phips/1xDeJPG_OmniSR",
+    "1xDeJPG_realplksr_otf": "Phips/1xDeJPG_realplksr_otf",
+    "1xDeJPG_SRFormer_light": "Phips/1xDeJPG_SRFormer_light",
+    "1xDeNoise_realplksr_otf": "Phips/1xDeNoise_realplksr_otf",
+    "1xExposureCorrection_compact": "Phips/1xExposureCorrection_compact",
+    "1xOverExposureCorrection_compact": "Phips/1xOverExposureCorrection_compact",
+    "1xUnderExposureCorrection_compact": "Phips/1xUnderExposureCorrection_compact",
+    "2xAoMR_mosr": "Phips/2xAoMR_mosr",
+    "2xEvangelion_compact": "Phips/2xEvangelion_compact",
+    "2xEvangelion_dat2": "Phips/2xEvangelion_dat2",
+    "2xEvangelion_omnisr": "Phips/2xEvangelion_omnisr",
+    "2xHFA2k_compact_multijpg": "Phips/2xHFA2k_compact_multijpg",
+    "2xHFA2k_LUDVAE_compact": "Phips/2xHFA2k_LUDVAE_compact",
+    "2xHFA2k_LUDVAE_SPAN": "Phips/2xHFA2k_LUDVAE_SPAN",
+    "2xHFA2kAVCCompact": "Phips/2xHFA2kAVCCompact",
+    "2xHFA2kAVCOmniSR": "Phips/2xHFA2kAVCOmniSR",
+    "2xHFA2kAVCSRFormer_light": "Phips/2xHFA2kAVCSRFormer_light",
+    "2xHFA2kCompact": "Phips/2xHFA2kCompact",
+    "2xHFA2kOmniSR": "Phips/2xHFA2kOmniSR",
+    "2xHFA2kReal-CUGAN": "Phips/2xHFA2kReal-CUGAN",
+    "2xHFA2kShallowESRGAN": "Phips/2xHFA2kShallowESRGAN",
+    "2xHFA2kSPAN": "Phips/2xHFA2kSPAN",
+    "2xHFA2kSwinIR-S": "Phips/2xHFA2kSwinIR-S",
+    "2xLexicaRRDBNet": "Phips/2xLexicaRRDBNet",
+    "2xLexicaRRDBNet_Sharp": "Phips/2xLexicaRRDBNet_Sharp",
+    "2xNomosUni_compact_multijpg": "Phips/2xNomosUni_compact_multijpg",
+    "2xNomosUni_compact_multijpg_ldl": "Phips/2xNomosUni_compact_multijpg_ldl",
+    "2xNomosUni_compact_otf_medium": "Phips/2xNomosUni_compact_otf_medium",
+    "2xNomosUni_esrgan_multijpg": "Phips/2xNomosUni_esrgan_multijpg",
+    "2xNomosUni_span_multijpg": "Phips/2xNomosUni_span_multijpg",
+    "2xNomosUni_span_multijpg_ldl": "Phips/2xNomosUni_span_multijpg_ldl",
+    "2xParimgCompact": "Phips/2xParimgCompact",
+    "4x4xTextures_GTAV_rgt-s": "Phips/4xTextures_GTAV_rgt-s",
+    "4xArtFaces_realplksr_dysample": "Phips/4xArtFaces_realplksr_dysample",
+    "4xBHI_dat2_multiblur": "Phips/4xBHI_dat2_multiblur",
+    "4xBHI_dat2_multiblurjpg": "Phips/4xBHI_dat2_multiblurjpg",
+    "4xBHI_dat2_otf": "Phips/4xBHI_dat2_otf",
+    "4xBHI_dat2_real": "Phips/4xBHI_dat2_real",
+    "4xBHI_realplksr_dysample_multi": "Phips/4xBHI_realplksr_dysample_multi",
+    "4xBHI_realplksr_dysample_multiblur": "Phips/4xBHI_realplksr_dysample_multiblur",
+    "4xBHI_realplksr_dysample_otf": "Phips/4xBHI_realplksr_dysample_otf",
+    "4xBHI_realplksr_dysample_otf_nn": "Phips/4xBHI_realplksr_dysample_otf_nn",
+    "4xBHI_realplksr_dysample_real": "Phips/4xBHI_realplksr_dysample_real",
+    "4xFaceUpDAT": "Phips/4xFaceUpDAT",
+    "4xFaceUpLDAT": "Phips/4xFaceUpLDAT",
+    "4xFaceUpSharpDAT": "Phips/4xFaceUpSharpDAT",
+    "4xFaceUpSharpLDAT": "Phips/4xFaceUpSharpLDAT",
+    "4xFFHQDAT": "Phips/4xFFHQDAT",
+    "4xFFHQLDAT": "Phips/4xFFHQLDAT",
+    "4xHFA2k": "Phips/4xHFA2k",
+    "4xHFA2k_ludvae_realplksr_dysample": "Phips/4xHFA2k_ludvae_realplksr_dysample",
+    "4xHFA2kLUDVAEGRL_small": "Phips/4xHFA2kLUDVAEGRL_small",
+    "4xHFA2kLUDVAESRFormer_light": "Phips/4xHFA2kLUDVAESRFormer_light",
+    "4xHFA2kLUDVAESwinIR_light": "Phips/4xHFA2kLUDVAESwinIR_light",
+    "4xLexicaDAT2_otf": "Phips/4xLexicaDAT2_otf",
+    "4xLSDIRCompact2": "Phips/4xLSDIRCompact2",
+    "4xLSDIRCompact": "Phips/4xLSDIRCompact",
+    "4xLSDIRCompactC3": "Phips/4xLSDIRCompactC3",
+    "4xLSDIRCompactC": "Phips/4xLSDIRCompactC",
+    "4xLSDIRCompactCR3": "Phips/4xLSDIRCompactCR3",
+    "4xLSDIRCompactN3": "Phips/4xLSDIRCompactN3",
+    "4xLSDIRCompactR3": "Phips/4xLSDIRCompactR3",
+    "4xLSDIRCompactR": "Phips/4xLSDIRCompactR",
+    "4xLSDIRDAT": "Phips/4xLSDIRDAT",
+    "4xNature_realplksr_dysample": "Phips/4xNature_realplksr_dysample",
+    "4xNomos2_hq_atd": "Phips/4xNomos2_hq_atd",
+    "4xNomos2_hq_dat2": "Phips/4xNomos2_hq_dat2",
+    "4xNomos2_hq_drct-l": "Phips/4xNomos2_hq_drct-l",
+    "4xNomos2_hq_mosr": "Phips/4xNomos2_hq_mosr",
+    "4xNomos2_otf_esrgan": "Phips/4xNomos2_otf_esrgan",
+    "4xNomos2_realplksr_dysample": "Phips/4xNomos2_realplksr_dysample",
+    "4xNomos8k_atd_jpg": "Phips/4xNomos8k_atd_jpg",
+    "4xNomos8kDAT": "Phips/4xNomos8kDAT",
+    "4xNomos8kHAT-L_bokeh_jpg": "Phips/4xNomos8kHAT-L_bokeh_jpg",
+    "4xNomos8kHAT-L_otf": "Phips/4xNomos8kHAT-L_otf",
+    "4xNomos8kSC": "Phips/4xNomos8kSC",
+    "4xNomos8kSCHAT-L": "Phips/4xNomos8kSCHAT-L",
+    "4xNomos8kSCHAT-S": "Phips/4xNomos8kSCHAT-S",
+    "4xNomos8kSCSRFormer": "Phips/4xNomos8kSCSRFormer",
+    "4xNomosUni_rgt_multijpg": "Phips/4xNomosUni_rgt_multijpg",
+    "4xNomosUni_rgt_s_multijpg": "Phips/4xNomosUni_rgt_s_multijpg",
+    "4xNomosUni_span_multijpg": "Phips/4xNomosUni_span_multijpg",
+    "4xNomosUniDAT2_box": "Phips/4xNomosUniDAT2_box",
+    "4xNomosUniDAT2_multijpg_ldl": "Phips/4xNomosUniDAT2_multijpg_ldl",
+    "4xNomosUniDAT2_multijpg_ldl_sharp": "Phips/4xNomosUniDAT2_multijpg_ldl_sharp",
+    "4xNomosUniDAT_bokeh_jpg": "Phips/4xNomosUniDAT_bokeh_jpg",
+    "4xNomosUniDAT_otf": "Phips/4xNomosUniDAT_otf",
+    "4xNomosWebPhoto_atd": "Phips/4xNomosWebPhoto_atd",
+    "4xNomosWebPhoto_esrgan": "Phips/4xNomosWebPhoto_esrgan",
+    "4xNomosWebPhoto_RealPLKSR": "Phips/4xNomosWebPhoto_RealPLKSR",
+    "4xReal_SSDIR_DAT_GAN": "Phips/4xReal_SSDIR_DAT_GAN",
+    "4xRealWebPhoto_v3_atd": "Phips/4xRealWebPhoto_v3_atd",
+    "4xRealWebPhoto_v4_dat2": "Phips/4xRealWebPhoto_v4_dat2",
+    "4xRealWebPhoto_v4_drct-l": "Phips/4xRealWebPhoto_v4_drct-l",
+    "4xSSDIRDAT": "Phips/4xSSDIRDAT",
+    "4xTextureDAT2_otf": "Phips/4xTextureDAT2_otf",
+    "4xTextures_GTAV_rgt-s": "Phips/4xTextures_GTAV_rgt-s",
+    "4xTextures_GTAV_rgt-s_dither": "Phips/4xTextures_GTAV_rgt-s_dither",
+}
+
+# --- Efficient Model Loading and Caching ---
+LOADED_MODELS_CACHE = {}
+
+def get_upscaler(model_name: str):
+    if model_name not in LOADED_MODELS_CACHE:
+        print(f"Loading model: {model_name}")
+        LOADED_MODELS_CACHE[model_name] = UpscaleWithModel.from_pretrained(
+            MODELS[model_name]
+        ).to("cuda")
+    return LOADED_MODELS_CACHE[model_name]
+
+# --- Core Upscaling Function ---
+@spaces.GPU
+def upscale_image(image, model_selection: str, progress=gr.Progress(track_tqdm=True)):
+    if image is None:
+        raise gr.Error("No image uploaded. Please upload an image to upscale.")
+
+    try:
+        progress(0, desc="Loading image and model...")
+        original = load_image(image)
+        upscaler = get_upscaler(model_selection)
+
+        progress(0.5, desc="Upscaling image... (this may take a moment)")
+        upscaled_pil_image = upscaler(original, tiling=True, tile_width=1024, tile_height=1024)
+
+        progress(0.9, desc="Saving result...")
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_file:
+            upscaled_pil_image.save(temp_file.name, "PNG")
+            output_filepath = temp_file.name
+
+        return (original, upscaled_pil_image), output_filepath
+
+    except Exception as e:
+        print(f"An error occurred: {traceback.format_exc()}")
+        raise gr.Error(f"An error occurred during processing: {e}")
+
+def clear_outputs():
+    return None, None
+
+# --- Gradio Interface Definition ---
+title = """<h1 align="center">Image Upscaler</h1>
+<div align="center">
+Use this Space to upscale your images with a collection of custom-trained models.<br>
+This app uses the <a href="https://github.com/asomoza/image_gen_aux">Image Generation Auxiliary Tools</a> library and <a href="https://github.com/Phhofm/models">my models</a>.<br>
+Tiling is fixed at 1024x1024 for optimal performance. An <a href="https://huggingface.co/spaces/Phips/Upscaler/resolve/main/input_example1.png">example input image</a> is available to try.
+</div>
+"""
+
+with gr.Blocks(delete_cache=(3600, 3600)) as demo:
+    gr.HTML(title)
+    with gr.Row():
+        with gr.Column(scale=1):
+            input_image = gr.Image(type="pil", label="Input Image")
+            model_selection = gr.Dropdown(
+                choices=list(MODELS.keys()),
+                value="4xBHI_dat2_real",
+                label="Model (alphabetically sorted)",
+            )
+            run_button = gr.Button("Upscale", variant="primary")
+            
+        with gr.Column(scale=2):
+            result_slider = ImageSlider(
+                interactive=False,
+                label="Compare Original vs. Upscaled",
+                show_label=True,
+                show_download_button=False 
+            )
+            
+            # --- THIS IS THE NEW ADDITION ---
+            # Add a descriptive note to guide the user about the preview vs. download quality.
+            gr.Markdown(
+                "<center><i>Note: The slider above shows a web-optimized preview. For the full-quality, lossless PNG, please use the download button below.</i></center>"
+            )
+            
+            download_output = gr.File(label="Download Full-Quality Upscaled Image (Lossless PNG)")
+
+    # --- Event Handling ---
+    run_button.click(
+        fn=clear_outputs,
+        inputs=None,
+        outputs=[result_slider, download_output],
+        queue=False 
+    ).then(
+        fn=upscale_image,
+        inputs=[input_image, model_selection],
+        outputs=[result_slider, download_output],
+    )
+
+# --- Pre-load the default model for a faster first-time user experience ---
+try:
+    print("Pre-loading default model...")
+    get_upscaler("4xNomosWebPhoto_RealPLKSR")
+    print("Default model loaded successfully.")
+except Exception as e:
+    print(f"Could not pre-load the default model. The app will still work. Error: {e}")
+
+# Queueing is essential for public-facing apps to handle concurrent users.
+demo.queue()
+demo.launch(share=False)

requirements.txt

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+# Core deep learning library
+torch
+
+# Gradio for the web interface
+gradio
+gradio-imageslider
+
+# The upscaling library
+git+https://github.com/asomoza/image_gen_aux.git