Update app.py

app.py

@@ -48,42 +48,11 @@ class OrangeRedTheme(Soft):
             font=font,
             font_mono=font_mono,
         )
-        super().set(
-            background_fill_primary="*primary_50",
-            background_fill_primary_dark="*primary_900",
-            body_background_fill="linear-gradient(135deg, *primary_200, *primary_100)",
-            body_background_fill_dark="linear-gradient(135deg, *primary_900, *primary_800)",
-            button_primary_text_color="white",
-            button_primary_text_color_hover="white",
-            button_primary_background_fill="linear-gradient(90deg, *secondary_500, *secondary_600)",
-            button_primary_background_fill_hover="linear-gradient(90deg, *secondary_600, *secondary_700)",
-            button_primary_background_fill_dark="linear-gradient(90deg, *secondary_600, *secondary_700)",
-            button_primary_background_fill_hover_dark="linear-gradient(90deg, *secondary_500, *secondary_600)",
-            button_secondary_text_color="black",
-            button_secondary_text_color_hover="white",
-            button_secondary_background_fill="linear-gradient(90deg, *primary_300, *primary_300)",
-            button_secondary_background_fill_hover="linear-gradient(90deg, *primary_400, *primary_400)",
-            button_secondary_background_fill_dark="linear-gradient(90deg, *primary_500, *primary_600)",
-            button_secondary_background_fill_hover_dark="linear-gradient(90deg, *primary_500, *primary_500)",
-            slider_color="*secondary_500",
-            slider_color_dark="*secondary_600",
-            block_title_text_weight="600",
-            block_border_width="3px",
-            block_shadow="*shadow_drop_lg",
-            button_primary_shadow="*shadow_drop_lg",
-            button_large_padding="11px",
-            color_accent_soft="*primary_100",
-            block_label_background_fill="*primary_200",
-        )
 
 orange_red_theme = OrangeRedTheme()
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-print("CUDA_VISIBLE_DEVICES=", os.environ.get("CUDA_VISIBLE_DEVICES"))
-print("torch.__version__ =", torch.__version__)
-print("Using device:", device)
-
 from diffusers import FlowMatchEulerDiscreteScheduler
 from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
 from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
@@ -96,14 +65,13 @@ pipe = QwenImageEditPlusPipeline.from_pretrained(
     transformer=QwenImageTransformer2DModel.from_pretrained(
         "prithivMLmods/Qwen-Image-Edit-Rapid-AIO-V19",
         torch_dtype=dtype,
-        device_map='cuda'
+        device_map="cuda"
     ),
     torch_dtype=dtype
 ).to(device)
 
 try:
     pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
-    print("Flash Attention 3 Processor set successfully.")
 except Exception as e:
     print(f"Warning: Could not set FA3 processor: {e}")
 
@@ -150,61 +118,6 @@ ADAPTER_SPECS = {
         "weights": "anything2real_2601.safetensors",
         "adapter_name": "anything2real"
     },
-    "Fal-Multiple-Angles": {
-        "repo": "fal/Qwen-Image-Edit-2511-Multiple-Angles-LoRA",
-        "weights": "qwen-image-edit-2511-multiple-angles-lora.safetensors",
-        "adapter_name": "fal-multiple-angles"
-    },
-    "Polaroid-Photo": {
-        "repo": "prithivMLmods/Qwen-Image-Edit-2511-Polaroid-Photo",
-        "weights": "Qwen-Image-Edit-2511-Polaroid-Photo.safetensors",
-        "adapter_name": "polaroid-photo"
-    },
-    "Unblur-Anything": {
-        "repo": "prithivMLmods/Qwen-Image-Edit-2511-Unblur-Upscale",
-        "weights": "Qwen-Image-Edit-Unblur-Upscale_15.safetensors",
-        "adapter_name": "unblur-anything"
-    },
-    "Midnight-Noir-Eyes-Spotlight": {
-        "repo": "prithivMLmods/Qwen-Image-Edit-2511-Midnight-Noir-Eyes-Spotlight",
-        "weights": "Qwen-Image-Edit-2511-Midnight-Noir-Eyes-Spotlight.safetensors",
-        "adapter_name": "midnight-noir-eyes-spotlight"
-    },
-    "Hyper-Realistic-Portrait": {
-       "repo": "prithivMLmods/Qwen-Image-Edit-2511-Hyper-Realistic-Portrait",
-       "weights": "HRP_20.safetensors",
-       "adapter_name": "hyper-realistic-portrait"
-   },     
-    "Ultra-Realistic-Portrait": {
-       "repo": "prithivMLmods/Qwen-Image-Edit-2511-Ultra-Realistic-Portrait",
-       "weights": "URP_20.safetensors",
-       "adapter_name": "ultra-realistic-portrait"
-   },     
-    "Pixar-Inspired-3D": {
-       "repo": "prithivMLmods/Qwen-Image-Edit-2511-Pixar-Inspired-3D",
-       "weights": "PI3_20.safetensors",
-       "adapter_name": "pi3"
-   },
-    "Noir-Comic-Book": {
-       "repo": "prithivMLmods/Qwen-Image-Edit-2511-Noir-Comic-Book-Panel",
-       "weights": "Noir-Comic-Book-Panel_20.safetensors",
-       "adapter_name": "ncb"
-   },  
-    "Any-light": {
-       "repo": "lilylilith/QIE-2511-MP-AnyLight",
-       "weights": "QIE-2511-AnyLight_.safetensors",
-       "adapter_name": "any-light"
-   }, 
-    "Studio-DeLight": {
-       "repo": "prithivMLmods/QIE-2511-Studio-DeLight",
-       "weights": "QIE-2511-Studio-DeLight-5000.safetensors",
-       "adapter_name": "studio-delight"
-   }, 
-    "Cinematic-FlatLog": {
-       "repo": "prithivMLmods/QIE-2511-Cinematic-FlatLog-Control",
-       "weights": "QIE-2511-Cinematic-FlatLog-Control-3200.safetensors",
-       "adapter_name": "flat-log"
-   },   
 }
 
 LOADED_ADAPTERS = set()
@@ -212,28 +125,26 @@ LOADED_ADAPTERS = set()
 def update_dimensions_on_upload(image):
     if image is None:
         return 1024, 1024
-    
+
     original_width, original_height = image.size
-    
+
     if original_width > original_height:
         new_width = 1024
-        aspect_ratio = original_height / original_width
-        new_height = int(new_width * aspect_ratio)
+        new_height = int(new_width * (original_height / original_width))
     else:
         new_height = 1024
-        aspect_ratio = original_width / original_height
-        new_width = int(new_height * aspect_ratio)
-        
+        new_width = int(new_height * (original_width / original_height))
+
     new_width = (new_width // 8) * 8
     new_height = (new_height // 8) * 8
-    
+
     return new_width, new_height
 
+
 @spaces.GPU
 def infer(
     images,
     prompt,
-    lora_adapter,
     seed,
     randomize_seed,
     guidance_scale,
@@ -244,49 +155,40 @@ def infer(
     torch.cuda.empty_cache()
 
     if not images:
-        raise gr.Error("Please upload at least one image to edit.")
+        raise gr.Error("Please upload an image.")
 
     pil_images = []
-    if images is not None:
-        for item in images:
-            try:
-                if isinstance(item, tuple) or isinstance(item, list):
-                    path_or_img = item[0]
-                else:
-                    path_or_img = item
-
-                if isinstance(path_or_img, str):
-                    pil_images.append(Image.open(path_or_img).convert("RGB"))
-                elif isinstance(path_or_img, Image.Image):
-                    pil_images.append(path_or_img.convert("RGB"))
-                else:
-                    pil_images.append(Image.open(path_or_img.name).convert("RGB"))
-            except Exception as e:
-                print(f"Skipping invalid image item: {e}")
-                continue
 
-    if not pil_images:
-        raise gr.Error("Could not process uploaded images.")
+    for item in images:
+        try:
+            if isinstance(item, tuple) or isinstance(item, list):
+                path_or_img = item[0]
+            else:
+                path_or_img = item
+
+            if isinstance(path_or_img, str):
+                pil_images.append(Image.open(path_or_img).convert("RGB"))
+            elif isinstance(path_or_img, Image.Image):
+                pil_images.append(path_or_img.convert("RGB"))
+            else:
+                pil_images.append(Image.open(path_or_img.name).convert("RGB"))
+        except Exception:
+            continue
 
-    spec = ADAPTER_SPECS.get(lora_adapter)
-    if not spec:
-        raise gr.Error(f"Configuration not found for: {lora_adapter}")
+    if not pil_images:
+        raise gr.Error("Could not process uploaded image.")
 
+    # LOCKED STYLE
+    spec = ADAPTER_SPECS["Anything2Real"]
     adapter_name = spec["adapter_name"]
 
     if adapter_name not in LOADED_ADAPTERS:
-        print(f"--- Downloading and Loading Adapter: {lora_adapter} ---")
-        try:
-            pipe.load_lora_weights(
-                spec["repo"], 
-                weight_name=spec["weights"], 
-                adapter_name=adapter_name
-            )
-            LOADED_ADAPTERS.add(adapter_name)
-        except Exception as e:
-            raise gr.Error(f"Failed to load adapter {lora_adapter}: {e}")
-    else:
-        print(f"--- Adapter {lora_adapter} is already loaded. ---")
+        pipe.load_lora_weights(
+            spec["repo"],
+            weight_name=spec["weights"],
+            adapter_name=adapter_name
+        )
+        LOADED_ADAPTERS.add(adapter_name)
 
     pipe.set_adapters([adapter_name], adapter_weights=[1.0])
 
@@ -294,136 +196,87 @@ def infer(
         seed = random.randint(0, MAX_SEED)
 
     generator = torch.Generator(device=device).manual_seed(seed)
-    negative_prompt = "worst quality, low quality, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry"
 
     width, height = update_dimensions_on_upload(pil_images[0])
 
-    try:
-        result_image = pipe(
-            image=pil_images,
-            prompt=prompt,
-            negative_prompt=negative_prompt,
-            height=height,
-            width=width,
-            num_inference_steps=steps,
-            generator=generator,
-            true_cfg_scale=guidance_scale,
-        ).images[0]
-        
-        return result_image, seed
-
-    except Exception as e:
-        raise e
-    finally:
-        gc.collect()
-        torch.cuda.empty_cache()
-
-@spaces.GPU
-def infer_example(images, prompt, lora_adapter):
-    if not images:
-        return None, 0
-    
-    if isinstance(images, str):
-        images_list = [images]
-    else:
-        images_list = images
-        
-    result, seed = infer(
-        images=images_list,
+    result_image = pipe(
+        image=pil_images,
         prompt=prompt,
-        lora_adapter=lora_adapter,
-        seed=0,
-        randomize_seed=True,
-        guidance_scale=1.0,
-        steps=4
-    )
-    return result, seed
+        negative_prompt="worst quality, blurry, watermark",
+        height=height,
+        width=width,
+        num_inference_steps=steps,
+        generator=generator,
+        true_cfg_scale=guidance_scale,
+    ).images[0]
+
+    gc.collect()
+    torch.cuda.empty_cache()
+
+    return result_image, seed
 
-css="""
+
+css = """
 #col-container {
     margin: 0 auto;
-    max-width: 1000px;
+    max-width: 850px;
+}
+#main-title h1 {
+    font-size: 2.4em !important;
+    text-align: center;
 }
-#main-title h1 {font-size: 2.4em !important;}
 """
 
-with gr.Blocks() as demo:
+with gr.Blocks(theme=orange_red_theme, css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown("# **Qwen-Image-Edit-2511-LoRAs-Fast**", elem_id="main-title")
-        gr.Markdown("Perform diverse image edits using specialized [LoRA](https://huggingface.co/models?other=base_model:adapter:Qwen/Qwen-Image-Edit-2511) adapters. Open on [GitHub](https://github.com/PRITHIVSAKTHIUR/Qwen-Image-Edit-2511-LoRAs-Fast-Lazy-Load).")
-
-        with gr.Row(equal_height=True):
-            with gr.Column():
-                images = gr.Gallery(
-                    label="Upload Images", 
-                    type="filepath", 
-                    columns=2, 
-                    rows=1, 
-                    height=300,
-                    allow_preview=True
-                )
-                
-                prompt = gr.Text(
-                    label="Edit Prompt",
-                    #max_lines=1,
-                    show_label=True,
-                    placeholder="e.g., transform into anime..",
-                )
-
-                run_button = gr.Button("Edit Image", variant="primary")
-
-            with gr.Column():
-                output_image = gr.Image(label="Output Image", interactive=False, format="png", height=365)
-                
-                with gr.Row():
-                    lora_adapter = gr.Dropdown(
-                        label="Choose Editing Style",
-                        choices=list(ADAPTER_SPECS.keys()),
-                        value="Photo-to-Anime"
-                    )
-                
-                with gr.Accordion("Advanced Settings", open=False, visible=False):
-                    seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
-                    randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
-                    guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=1.0)
-                    steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=4)
-        
-        gr.Examples(
-            examples=[
-                [["examples/B.jpg"], "Transform into anime.", "Photo-to-Anime"],
-                [["examples/HRP.jpg"], "Transform into a hyper-realistic face portrait.", "Hyper-Realistic-Portrait"],
-                [["examples/A.jpeg"], "Rotate the camera 45 degrees to the right.", "Multiple-Angles"],
-                [["examples/U.jpg"], "Upscale this picture to 4K resolution.", "Upscaler"],
-                [["examples/L1.jpg", "examples/L2.jpg"], "Apply the lighting from image 2 to image 1.", "Any-light"],
-                [["examples/PP1.jpg"], "cinematic polaroid with soft grain subtle vignette gentle lighting white frame handwritten photographed by hf‪‪‬ preserving realistic texture and details", "Polaroid-Photo"],
-                [["examples/Z1.jpg"], "Front-right quarter view.", "Fal-Multiple-Angles"],
-                [["examples/URP.jpg"], "Transform into a cinematic flat log.", "Cinematic-FlatLog"],
-                [["examples/SL.jpg"], "Neutral uniform lighting Preserve identity and composition.", "Studio-DeLight"],
-                [["examples/PI.jpg"], "Transform it into Pixar-inspired 3D.", "Pixar-Inspired-3D"],
-                [["examples/MT.jpg"], "Paint with manga tone.", "Manga-Tone"],
-                [["examples/NCB.jpg"], "Transform into a noir comic book style.", "Noir-Comic-Book"],
-                [["examples/URP.jpg"], "ultra-realistic portrait.", "Ultra-Realistic-Portrait"],
-                [["examples/MN.jpg"], "Transform into Midnight Noir Eyes Spotlight.", "Midnight-Noir-Eyes-Spotlight"],
-                [["examples/ST1.jpg", "examples/ST2.jpg"], "Convert Image 1 to the style of Image 2.", "Style-Transfer"],
-                [["examples/R1.jpg"], "Change the picture to realistic photograph.", "Anything2Real"],
-                [["examples/UA.jpeg"], "Unblur and upscale.", "Unblur-Anything"],
-                [["examples/L1.jpg", "examples/L2.jpg"], "Refer to the color tone, remove the original lighting from Image 1, and relight Image 1 based on the lighting and color tone of Image 2.", "Light-Migration"],
-                [["examples/P1.jpg"], "Transform into anime (while preserving the background and remaining elements maintaining realism and original details.)", "Anime-V2"],
-            ],
-            inputs=[images, prompt, lora_adapter],
-            outputs=[output_image, seed],
-            fn=infer_example,
-            cache_examples=False,
-            label="Examples"
+        gr.Markdown("# **Image Nsfw Editor**", elem_id="main-title")
+        gr.Markdown("Upload an image and transform it into NSFW.")
+
+        input_image = gr.Gallery(
+            label="Upload Image",
+            type="filepath",
+            columns=1,
+            rows=1,
+            height=350,
+            allow_preview=True
+        )
+
+        prompt = gr.Textbox(
+            label="Prompt",
+            placeholder="Describe the realistic transformation..."
         )
-        
-        gr.Markdown("[*](https://huggingface.co/spaces/prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast)This is still an experimental Space for Qwen-Image-Edit-2511.")
+
+        run_button = gr.Button("Generate", variant="primary")
+
+        output_image = gr.Image(
+            label="Output",
+            interactive=False,
+            format="png",
+            height=500
+        )
+
+        # hidden backend essentials
+        seed = gr.State(0)
+        randomize_seed = gr.State(True)
+        guidance_scale = gr.State(1.0)
+        steps = gr.State(4)
 
     run_button.click(
         fn=infer,
-        inputs=[images, prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps],
+        inputs=[
+            input_image,
+            prompt,
+            seed,
+            randomize_seed,
+            guidance_scale,
+            steps
+        ],
         outputs=[output_image, seed]
     )
 
 if __name__ == "__main__":
-    demo.queue(max_size=30).launch(css=css, theme=orange_red_theme, mcp_server=True, ssr_mode=False, show_error=True)
+    demo.queue(max_size=30).launch(
+        mcp_server=True,
+        ssr_mode=False,
+        show_error=True
+    )