Update app.py

app.py

@@ -44,7 +44,7 @@ def predict_clothing(images):
     
 
 @spaces.GPU(duration=180)
-def generate_image(img1, img2, img3, height, width, img_guidance_scale, inference_steps, seed, separate_cfg_infer, offload_model,
+def generate_image(category, img1, img2, img3, height, width, img_guidance_scale, inference_steps, seed, separate_cfg_infer, offload_model,
                    use_input_image_size_as_output, max_input_image_size, randomize_seed, guidance_scale=3):
 
     print()
@@ -57,10 +57,10 @@ def generate_image(img1, img2, img3, height, width, img_guidance_scale, inferenc
     wears = predict_clothing(input_images[1:])
     if len(wears)==1:
         dress = wears[0]
-        text = f"""A male wearing a {dress}. The male is in <img><|image_1|></img>. The {dress} is in <img><|image_2|></img>."""
+        text = f"""The {category} in <img><|image_1|></img> is wearing a {dress}. The {dress} is in <img><|image_2|></img>."""
     elif len(wears)==2:
         topwear, bottomwear = wears[0], wears[1]
-        text = f"""A male wearing a {topwear} and a {bottomwear}. The male is in <img><|image_1|></img>.
+        text = f"""The {category} in <img><|image_1|></img> is wearing a {topwear} and a {bottomwear}.
                     The {topwear} is in <img><|image_2|></img>. The {bottomwear} is in <img><|image_3|></img>."""
     else:
         input_images = None
@@ -103,8 +103,8 @@ def run_for_examples(img1, img2, img3, height, width, img_guidance_scale, seed,
     offload_model = False
 
     text = "According to the following examples, generate an output for the input.\nInput: <img><|image_1|></img>\nOutput: <img><|image_2|></img>\n\nInput: <img><|image_3|></img>\nOutput:"
-    return generate_image(text, img1, img2, img3, height, width, img_guidance_scale, inference_steps, seed,
-                          separate_cfg_infer, offload_model, use_input_image_size_as_output, max_input_image_size, randomize_seed, guidance_scale)
+    return generate_image(img1, img2, img3, height, width, img_guidance_scale, inference_steps, seed, separate_cfg_infer,
+                          offload_model, use_input_image_size_as_output, max_input_image_size, randomize_seed)
 
 
 description = """
@@ -140,9 +140,9 @@ with gr.Blocks() as demo:
 
     with gr.Row():
         with gr.Column():
-            # sliders
-            max_input_image_size = gr.Slider(label="max_input_image_size", minimum=128, maximum=2048, value=1024, step=16)
+            category = gr.Radio(["man", "woman", "boy", "girl"], label="Category", info="Choose one category from the following")
             
+            # sliders            
             height_input = gr.Slider(label="Height", minimum=128, maximum=1024, value=512, step=16)
             width_input = gr.Slider(label="Width", minimum=128, maximum=1024, value=512, step=16)
     
@@ -154,6 +154,8 @@ with gr.Blocks() as demo:
             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
 
         with gr.Column():
+            max_input_image_size = gr.Slider(label="max_input_image_size", minimum=128, maximum=2048, value=1024, step=16)
+            
             img_guidance_scale_input = gr.Slider(label="img_guidance_scale", minimum=1.0, maximum=2.0, value=1.6, step=0.1)
             
             separate_cfg_infer = gr.Checkbox(
@@ -176,7 +178,7 @@ with gr.Blocks() as demo:
     # click
     generate_button.click(
         generate_image,
-        inputs=[image_input_1, image_input_2, image_input_3, height_input, width_input, img_guidance_scale_input, num_inference_steps,
+        inputs=[category, image_input_1, image_input_2, image_input_3, height_input, width_input, img_guidance_scale_input, num_inference_steps,
                 seed_input, separate_cfg_infer, offload_model, use_input_image_size_as_output, max_input_image_size, randomize_seed,],
         outputs=output_image,
     )