init

README.md

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+---
+title: Colabor-Image-Finetune
+emoji: 💻
+colorFrom: purple
+colorTo: indigo
+sdk: gradio
+sdk_version: 5.29.0
+app_file: app.py
+pinned: false
+short_description: Fine-tuned image to create artworks of persona
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import replicate
+import os
+import json
+import gradio as gr
+import requests
+
+fish_api_key = os.getenv("FISH_API_KEY")
+
+def load_config(config_path="config.json"):
+    """Load configuration from JSON file"""
+    with open(config_path, 'r') as f:
+        return json.load(f)
+    
+config = load_config()
+api_token = os.getenv("REPLICATE_API_TOKEN")
+
+#api_token =config["replicate_api_token"]
+#os.environ["REPLICATE_API_TOKEN"] = api_token
+
+def save_image(output):
+    file_path = "generated_image.png"
+    image_url = output[0]
+    response = requests.get(image_url)
+    # Save the image
+    with open(file_path, "wb") as file:
+        file.write(response.content)
+    
+    return file_path
+
+def generate(lora_model, prompt, aspect_ratio, num_inference_steps, guidance_scale, seed, lora_scale):
+    selected_lora_model = config["image_model"][lora_model]["persona"]
+    trigger_word = config["image_model"][lora_model]["trigger_word"]
+
+    input = {
+        "model": "dev",
+        "prompt": f'{trigger_word} + " "  + {prompt} + " " + in the style of + " " + {trigger_word}',
+        "go_fast": False,
+        "lora_scale": lora_scale,
+        "num_outputs": 1,
+        "aspect_ratio": aspect_ratio,
+        "output_format": "png",
+        "guidance_scale": guidance_scale,
+        "extra_lora_scale": lora_scale,
+        "num_inference_steps": num_inference_steps,
+        "seed": int(seed) if int(seed) != -1 else -1,
+     
+    }
+
+    output = replicate.run(
+        selected_lora_model,
+        input=input
+    )
+    
+    image_path = save_image(output)
+    return image_path
+        
+# Create Gradio interface
+def create_interface():
+
+    with gr.Blocks(title="Image Generator") as interface:
+        gr.Markdown("# LoRA Image Generator")
+        
+        with gr.Row():
+            with gr.Column():
+                lora_model = gr.Dropdown(
+                    choices= ["group1", "group2", "group3", "group4", "group5"],
+                    label="Choose your Image Model"
+                )
+                prompt = gr.Textbox(
+                    label="Prompt", 
+
+                )
+                aspect_ratio = gr.Dropdown(
+                    choices=["1:1", "16:9", "9:16"], 
+                    label="Aspect Ratio", 
+                    value="1:1"
+                )
+                num_inference_steps = gr.Slider(
+                    minimum=1, 
+                    maximum=50, 
+                    value=28, 
+                    step=1, 
+                    label="Inference Steps"
+                )
+                guidance_scale = gr.Slider(
+                    minimum=0, 
+                    maximum=10, 
+                    value=3, 
+                    step=1, 
+                    label="Guidance Scale"
+                )
+                seed = gr.Number(
+                    label="Seed (-1 for random)", 
+                    value=-1.0
+                )
+                lora_scale = gr.Slider(
+                    minimum=-1.0, 
+                    maximum=3.0, 
+                    value=1.0, 
+                    step=0.05, 
+                    label="LoRA Scale"
+                )
+                generate_btn = gr.Button("Generate Image")
+            
+            with gr.Column():
+                output_image = gr.Image(label="Generated Image")
+        
+        generate_btn.click(
+            fn=generate,
+            inputs=[lora_model, prompt, aspect_ratio, num_inference_steps, 
+                   guidance_scale, seed, lora_scale],
+            outputs=output_image
+        )
+    
+    return interface
+
+if __name__ == "__main__":
+    interface = create_interface()
+    interface.launch()

config.json

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+{
+    "image_model": {
+      "group1" : {
+        "persona":"kratadata/persona1:c44c75daebd6dc27d65a43322ad8440479bf2dfc77e7fb4d670f02c2bf2a5a00",
+        "trigger_word": "TOK"
+      },
+      "group2" : {
+        "persona":"kratadata/persona2:8b40b98ccbf3d6080e955cf7a9e5a83e6306f85169c1d127db2b0104f29b571e",
+        "trigger_word":"picaka"
+      },
+      "group3" : {
+        "persona": "kratadata/persona3:c593b245347d9b030eda2cdb8955d9122c3281620a268ceb4bb6e18845a3bfb3",  
+        "trigger_word" : "kAi"
+      },
+      "group4" : {
+        "persona": "kratadata/persona4:ac804d11ee98507be0e5dfa8c3a9dc112a0b88fb97a2eb4d3b79142477180e76",  
+        "trigger_word" : "TUMULU"
+      },
+      "group5" : {
+        "persona": "kratadata/persona5:34b9586bb90f50f5b598b50d7781142e4cc5dcc1b32d2f4eae4b4379404f5f3e",  
+        "trigger_word" : "JSCA"
+      }
+    
+    }
+}

requirements.tx

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+replicate