Add input fields guidance and inference - Convert image to jpg

app.py

@@ -6,6 +6,8 @@ import os
 from diffusers import AutoPipelineForText2Image
 import torch
 from huggingface_hub import snapshot_download
+from io import BytesIO
+from PIL import Image
 
 SPACE_USERNAME = 'KR_4dmin'
 SPACE_PASSWORD = 'KR_4dmin'
@@ -22,20 +24,23 @@ MAX_IMAGE_SIZE = 1024
 
 
 @spaces.GPU
-def infer(prompt, height, width):
-
-    # init_image = refer_image.resize((1024, 1024))
+def infer(prompt, height, width, guidance_scale, num_inference_steps):
 
     image = pipeline(
         prompt=prompt,
-        # guidance_scale=guidance_scale,
-        # num_inference_steps=num_inference_steps,
+        guidance_scale=guidance_scale,
+        num_inference_steps=num_inference_steps,
         width=width,
         height=height,
         # image=refer_image
         # generator=generator
     ).images[0]
 
+    # Convert the image to JPG format
+    img_byte_arr = BytesIO()
+    image.save(img_byte_arr, format='JPEG')
+    img_byte_arr = img_byte_arr.getvalue()
+
     return image
 
 
@@ -107,20 +112,22 @@ with gr.Blocks(css=css) as demo:
 
                 guidance_scale = gr.Slider(
                     label="Guidance scale",
+                    info="Valores mas altos se apega mas al prompt, la calidad del resultado baja. Valores bajos permite creatividad pero se aleja del prompt",
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
-                    visible=False
+                    value=7.0,
+                    visible=True
                 )
 
                 num_inference_steps = gr.Slider(
                     label="Number of inference steps",
+                    info="Entre mas numeros de inferencia mejor calidad de la imagen. Toma mas tiempo generar la imagen.",
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=2,  # Replace with defaults that work for your model
-                    visible=False
+                    value=50,
+                    visible=True
                 )
 
         gr.Examples(
@@ -131,7 +138,7 @@ with gr.Blocks(css=css) as demo:
     gr.on(
         triggers=[run_button.click, prompt.submit],
         fn=infer,
-        inputs=[prompt, height, width],
+        inputs=[prompt, height, width, guidance_scale, num_inference_steps],
         outputs=[result]
     )