update static files

app.py

@@ -7,11 +7,10 @@ from diffsynth.pipelines.z_image import (
 )
 from diffsynth.pipelines.z_image import ZImagePipeline as ZImagePipelineDs
 from diffusers import ZImagePipeline
-from safetensors.torch import save_file, load_file
+from safetensors.torch import save_file
 import torch
 from PIL import Image
 from pathlib import Path
-from utils import repo_utils, image_utils, prompt_utils
 from huggingface_hub import snapshot_download
 import glob
 
@@ -173,16 +172,20 @@ def generate_lora(
         return False
 
     progress(0.1, desc="Processing images...")
+    print("progress: step 1")
     pil_images = [Image.open(filepath).convert("RGB") for filepath, _ in input_images]
 
     progress(0.3, desc="Encoding images to LoRA...")
+    print("progress: step 2")
     # Model inference
     with torch.no_grad():
         embs = ZImageUnit_Image2LoRAEncode().process(pipe_lora, image2lora_images=pil_images)
         progress(0.7, desc="Decoding LoRA weights...")
+        print("progress: step 3")
         lora = ZImageUnit_Image2LoRADecode().process(pipe_lora, **embs)["lora"]
 
     progress(0.9, desc="Saving LoRA file...")
+    print("progress: step 4")
     lora_name = f"{ulid}.safetensors"
     lora_path = f"loras/{lora_name}"
 

static/static/footer.md

@@ -0,0 +1,43 @@
+
+
+## Step by ste instruction
+- **Use jpg format**, upload a minimum 1 image to "Input Images".
+- Press "Generate LoRA".
+- After a moment, your LoRA will be ready to download.
+- Press "Generate image" to use LoRA above.
+The generated image will have similar style as the sample images you uploaded.
+
+If you're using Python, you can use the LoRA above to generate an image using instructions from DiffSynth-Studio (link below).
+
+**And if you're happy with the result, please support me by pressing the like button 😄**
+
+## For ComfyUI
+- Download the generated LoRA.
+- Use this sample workflow: <https://files.catbox.moe/4c6w5f.json>
+- Replace the lightning LoRA with the LoRA you've been downloaded before.
+
+Credit to *u/GBJI* from Reddit for the workflow.
+
+## Question and Answer
+**What can this app do?**  
+This demo helps you make new pictures that look like your example pictures, using a LoRA.
+
+**What is a lora?**  
+A LoRA (Low-Rank Adaptation) is a small add-on for a pre-trained image generation model. It's trained on a specific set of images to teach the model a new style, character, or object without retraining the entire model.
+
+**Is it different from IP Adapter?**  
+Yes, it is different.  
+IP Adapters are for style transfer (making your image look like a reference image). LoRA is for fine-tuning (teaching the model new concepts or styles).
+
+## Features
+- Use a single image to generate LoRA (though more images are better).
+- You can download the LoRA you generate.
+- There's also an option to generate an image using the LoRA you created.
+
+## Speed
+- LoRA generation takes about 20 seconds (H200 ZeroGPU).
+- Image generation using LoRA takes about 50 seconds (maybe something wrong here).
+
+## References
+- **DiffSynth-Studio**: <https://huggingface.co/DiffSynth-Studio/Qwen-Image-i2L>
+

static/static/header.html

@@ -0,0 +1,11 @@
+<div style="text-align: center; max-width: 600px; margin: 0 auto;">
+    <h1>
+        Qwen Image to LoRA
+    </h1>
+    <div class="grid-container" >
+        <p>
+            Generate LoRA from a few images.
+            <br>
+            Demo by <a href="https://aisudo.com/" target="_blank">AiSudo</a> 😊 
+    </div>
+</div>