solution to multiple accesses

app.py

@@ -8,7 +8,7 @@ import matplotlib.pyplot as plt
 from PIL import Image
 import subprocess
 
-def calculate_depth(model_type, img):
+def calculate_depth(model_type, gan_type, slider, img):
 
     if not os.path.exists('temp'):
       os.system('mkdir temp')
@@ -51,10 +51,6 @@ def calculate_depth(model_type, img):
     out_im = Image.fromarray(formatted)
     out_im.save("Images/Input-Test/1_d.png", "PNG")
 
-    return out_im
-
-def wiggle_effect(slider, gan_type):
-
     dim = '256' 
     c_images = '1'
     name_output = 'out'
@@ -66,31 +62,27 @@ def wiggle_effect(slider, gan_type):
                     ])
     subprocess.run(["python",  "WiggleResults/split.py", "--dim", dim])
 
-    return [f'WiggleResults/'+ name_output + '.jpg',f'WiggleResults/' + name_output + '_0.gif']
+    return [out_im, f'WiggleResults/'+ name_output + '.jpg',f'WiggleResults/' + name_output + '_0.gif']
 
 
 with gr.Blocks() as demo:
     gr.Markdown("Start typing below and then click **Run** to see the output.")
     
-    
     ## Depth Estimation
     midas_models = ["DPT_Large","DPT_Hybrid","MiDaS_small"]
+    gan_models = ["Cycle","Cycle(half)","noCycle","noCycle-noCr","noCycle-noCr-noL1","OnlyGen"]
+
     inp = [gr.inputs.Dropdown(midas_models, default="MiDaS_small", label="Depth estimation model type")]
+    inp.append(gr.inputs.Dropdown(gan_models, default="Cycle", label="Different Gan trainings"))
+    inp.append(gr.Slider(1,15, default = 2, label='StepCycles',step= 1))
     with gr.Row():
         inp.append(gr.Image(type="pil", label="Input"))
-        out = gr.Image(type="pil", label="depth_estimation")
-    btn = gr.Button("Calculate depth")
+        out = [gr.Image(type="pil", label="depth_estimation")]
+    with gr.Row():
+        out.append(gr.Image(type="file", label="Output_images"))
+        out.append(gr.Image(type="file", label="Output_wiggle"))
+    btn = gr.Button("Calculate depth + wiggle")
     btn.click(fn=calculate_depth, inputs=inp, outputs=out)
 
 
-    ## Wigglegram
-    gan_models = ["Cycle","Cycle(half)","noCycle","noCycle-noCr","noCycle-noCr-noL1","OnlyGen"]
-    inp = [gr.Slider(1,15, default = 2, label='StepCycles',step= 1)]
-    inp.append(gr.inputs.Dropdown(gan_models, default="Cycle", label="Different Gan trainings"))
-    with gr.Row():
-        out = [ gr.Image(type="file", label="Output_images"), #TODO change to gallery 
-                gr.Image(type="file", label="Output_wiggle")]
-    btn = gr.Button("Generate Wigglegram")
-    btn.click(fn=wiggle_effect, inputs=inp, outputs=out)
-
 demo.launch()