Update app.py

app.py

@@ -1,30 +1,48 @@
 import gradio as gr
 import random
+import os
 
-#model = gr.load("models/prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA") # <-- This model is also working
+# model = gr.load("models/prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA") # <-- This model is also working
 model = gr.load("models/Purz/face-projection")
 
-def generate_image(text, seed):
+def generate_image(text, seed, width, height, guidance_scale, num_inference_steps):
     if seed is not None:
         random.seed(seed)
 
     if text in [example[0] for example in examples]:
         print(f"Using example: {text}")
 
-    return model(text)
+    result_image = model(text)
+    
+    print(f"Width: {width}, Height: {height}, Guidance Scale: {guidance_scale}, Inference Steps: {num_inference_steps}")
+    
+    return result_image
+
+def randomize_parameters():
+    seed = random.randint(0, 999999)
+    width = random.randint(512, 2048)
+    height = random.randint(512, 2048)
+    guidance_scale = round(random.uniform(0.1, 20.0), 1)
+    num_inference_steps = random.randint(1, 40)
+    
+    return seed, width, height, guidance_scale, num_inference_steps
 
 examples = [
-    ["Humanoid Cat Warrior, Full View", None],
-    ["Warhammer Sisterhood", None],
-    ["Future Robots war", None],
-    ["Fantasy dragon", None]
+    ["Humanoid Cat Warrior, Full View", *randomize_parameters()],
+    ["Warhammer Sisterhood", *randomize_parameters()],
+    ["Future Robots war", *randomize_parameters()],
+    ["Fantasy dragon", *randomize_parameters()],
 ]
 
 interface = gr.Interface(
     fn=generate_image,
     inputs=[
         gr.Textbox(label="Type here your imagination:", placeholder="Type or click an example..."),
-        gr.Slider(minimum=0, maximum=10000, step=1, label="Seed (optional)")
+        gr.Slider(label="Seed", minimum=0, maximum=999999, step=1),
+        gr.Slider(label="Width", minimum=512, maximum=2048, step=64, value=1024),
+        gr.Slider(label="Height", minimum=512, maximum=2048, step=64, value=1024),
+        gr.Slider(label="Guidance Scale", minimum=0.1, maximum=20.0, step=0.1, value=3.0),
+        gr.Slider(label="Number of inference steps", minimum=1, maximum=40, step=1, value=28),
     ],
     outputs=gr.Image(label="Generated Image"),
     examples=examples,