Update app.py

app.py

@@ -21,7 +21,6 @@ def text2image_latent(text,steps,width,height,images,diversity):
         image_str = image_str.replace("data:image/png;base64,","")
         decoded_bytes = base64.decodebytes(bytes(image_str, "utf-8"))
         img = Image.open(io.BytesIO(decoded_bytes))
-        #image_arrays.append(numpy.asarray(img))
         url = shortuuid.uuid()
         temp_dir = './tmp'
         if not os.path.exists(temp_dir):
@@ -39,8 +38,8 @@ def text2image_vqgan(text,width,height,style,steps,flavor):
     results = vqgan(text,width,height,style,steps,flavor)
     return([results])
 
-def text2image_diffusion(steps_diff, images_diff, weight, clip):
-    results = diffusion(steps_diff, images_diff, weight, clip)
+def text2image_diffusion(text,steps_diff, images_diff, weight, clip):
+    results = diffusion(text, steps_diff, images_diff, weight, clip)
     image_paths = []
     image_arrays = []
     for image in results:
@@ -107,5 +106,5 @@ with gr.Blocks() as mindseye:
     get_image_latent.click(text2image_latent, inputs=[text,steps,width,height,images,diversity], outputs=gallery)
     get_image_rudalle.click(text2image_rudalle, inputs=[text,aspect,model], outputs=gallery)
     get_image_vqgan.click(text2image_vqgan, inputs=[text,width_vq,height_vq,style,steps,flavor],outputs=gallery)
-    get_image_diffusion.click(text2image_diffusion, inputs=[steps_diff, images_diff, weight, clip],outputs=gallery)
+    get_image_diffusion.click(text2image_diffusion, inputs=[text, steps_diff, images_diff, weight, clip],outputs=gallery)
 mindseye.launch()