Update app.py

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 import random
 
-# Load each model separately
+
 model1 = gr.load("models/pimpilikipilapi1/NSFW_master")
 model2 = gr.load("models/prashanth970/flux-lora-uncensored")
 model3 = gr.load("models/DiegoJR1973/NSFW-TrioHMH-Flux")
@@ -10,13 +10,34 @@ def generate_images(text, seed, width, height, guidance_scale, num_inference_ste
     if seed is not None:
         random.seed(seed)
 
-    # Generate images using each model
-    result_image1 = model1(text)
-    result_image2 = model2(text)
-    result_image3 = model3(text)
+    result_image1 = model1(
+        text, 
+        width=width, 
+        height=height, 
+        guidance_scale=guidance_scale, 
+        num_inference_steps=num_inference_steps
+    )
+
+    result_image2 = model2(
+        text, 
+        width=width - 128 if width > 640 else width,
+        height=height - 128 if height > 640 else height,
+        guidance_scale=guidance_scale * 1.2,
+        num_inference_steps=max(1, num_inference_steps - 5)
+    )
+    
+
+    result_image3 = model3(
+        text, 
+        width=width + 128 if width < 1920 else width,
+        height=height + 128 if height < 1920 else height,
+        guidance_scale=max(0.1, guidance_scale * 0.8),
+        num_inference_steps=min(40, num_inference_steps + 5)
+    )
 
-    # Print parameters for debugging
-    print(f"Width: {width}, Height: {height}, Guidance Scale: {guidance_scale}, Inference Steps: {num_inference_steps}")
+    print(f"Model 1: Width={width}, Height={height}, Guidance Scale={guidance_scale}, Steps={num_inference_steps}")
+    print(f"Model 2: Width={width - 128}, Height={height - 128}, Guidance Scale={guidance_scale * 1.2}, Steps={max(1, num_inference_steps - 5)}")
+    print(f"Model 3: Width={width + 128}, Height={height + 128}, Guidance Scale={max(0.1, guidance_scale * 0.8)}, Steps={min(40, num_inference_steps + 5)}")
     
     return result_image1, result_image2, result_image3
 
@@ -40,11 +61,11 @@ interface = gr.Interface(
         gr.Slider(label="Number of inference steps", minimum=1, maximum=40, step=1, value=28),
     ],
     outputs=[
-        gr.Image(label="Output 01"),
-        gr.Image(label="Output 02"),
-        gr.Image(label="Output 03")
+        gr.Image(label="Generated Image 01"),
+        gr.Image(label="Generated Image 02"),
+        gr.Image(label="Generated Image 03")
     ],
-    description="Generate images with three different models. Please note that the models are running on the CPU, which might affect performance. Thank you for your patience!",
+    description="Generate images with three different models, each with slight variations. Please note that the models are running on the CPU, which might affect performance. Thank you for your patience!",
 )
 
-interface.launch()
+interface.launch()