Move all to gallery

app.py

@@ -29,20 +29,34 @@ def text2image_latent(text,steps,width,height,images,diversity):
         image_path = f'{temp_dir}/{url}.png'
         img.save(f'{temp_dir}/{url}.png')
         image_paths.append(image_path)
-    return(results[0],image_paths)
+    return(image_paths)
   
 def text2image_rudalle(text,aspect,model):
     image = rudalle(text,aspect,model)[0]
-    return(image)
+    return([image])
 
 def text2image_vqgan(text,width,height,style,steps,flavor):
     results = vqgan(text,width,height,style,steps,flavor)
-    return(results)
+    return([results])
 
 def text2image_diffusion(steps_diff, images_diff, weight, clip):
     results = diffusion(steps_diff, images_diff, weight, clip)
-    print(results)
-    return(results)
+    image_paths = []
+    image_arrays = []
+    for image in results:
+        image_str = image[0]
+        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):
+            os.makedirs(temp_dir, exist_ok=True)
+        image_path = f'{temp_dir}/{url}.png'
+        img.save(f'{temp_dir}/{url}.png')
+        image_paths.append(image_path)
+    return(image_paths)
 
 css_mt = {"margin-top": "1em"}
 
@@ -85,13 +99,13 @@ with gr.Blocks() as mindseye:
                     get_image_diffusion = gr.button("Generate Image",css=css_mt)
         with gr.Row():
             with gr.Tabs():
-                with gr.TabItem("Image output"):
-                    image = gr.outputs.Image()
+                #with gr.TabItem("Image output"):
+                #    image = gr.outputs.Image()
                 with gr.TabItem("Gallery output"):
                     gallery = gr.Gallery(label="Individual images")
     
-    get_image_latent.click(text2image_latent, inputs=[text,steps,width,height,images,diversity], outputs=[image,gallery])
-    get_image_rudalle.click(text2image_rudalle, inputs=[text,aspect,model], outputs=image)
-    get_image_vqgan.click(text2image_vqgan, inputs=[text,width_vq,height_vq,style,steps,flavor],outputs=image)
+    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)
 mindseye.launch()