Update app.py

app.py

@@ -3,44 +3,34 @@
 #model3 = gr.load("models/prashanth970/flux-lora-uncensored")
 
 import gradio as gr
-import random
-import os
 
+model1 = gr.load("models/pimpilikipilapi1/NSFW_master")
+model2 = gr.load("models/prashanth970/flux-lora-uncensored")
 
-model = gr.load("models/pimpilikipilapi1/NSFW_master")
 
-def generate_image(text, seed, width, height, guidance_scale, num_inference_steps):
-    if seed is not None:
-        random.seed(seed)
-
-    result_image = model(text)
-    
-    print(f"Width: {width}, Height: {height}, Guidance Scale: {guidance_scale}, Inference Steps: {num_inference_steps}")
-    
+def generate_image(text, selected_model):
+    if selected_model == "Model 1 (NSFW Master)":
+        result_image = model1(text)
+    elif selected_model == "Model 2 (Flux Lora Uncensored)":
+        result_image = model2(text)
+    else:
+        return "Invalid model selection."
     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
 
 interface = gr.Interface(
     fn=generate_image,
     inputs=[
         gr.Textbox(label="Type here your imagination:", placeholder="Type your prompt..."),
-        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),
+        gr.Radio(
+            ["Model 1 (NSFW Master)", "Model 2 (Flux Lora Uncensored)"],
+            label="Select Model",
+            value="Model 1 (NSFW Master)",
+        ),
     ],
     outputs=gr.Image(label="Generated Image"),
-    theme="NoCrypt/miku",
-    description="Sorry for the inconvenience. The model is currently running on the CPU, which might affect performance. We appreciate your understanding.",
+    theme="Yntec/HaleyCH_Theme_Orange",
+    description="Sorry for the inconvenience. The models are currently running on the CPU, which might affect performance. We appreciate your understanding.",
 )
 
-interface.launch()
+interface.launch()