Update app.py

app.py

@@ -1,4 +1,4 @@
-import gradio as gr
+:import gradio as gr
 import yolov7
 import subprocess
 import tempfile
@@ -11,11 +11,11 @@ import gradio as gr
 
     
 def image_fn(
-    image: gr.Image = None,
-    model_path: gr.Dropdown = None,
-    image_size: gr.Slider = 640,
-    conf_threshold: gr.Slider = 0.25,
-    iou_threshold: gr.Slider = 0.45,
+    image: gr.inputs.Image = None,
+    model_path: gr.inputs.Dropdown = None,
+    image_size: gr.inputs.Slider = 640,
+    conf_threshold: gr.inputs.Slider = 0.25,
+    iou_threshold: gr.inputs.Slider = 0.45,
 ):
     """
     YOLOv7 inference function
@@ -41,8 +41,8 @@ def image_fn(
 image_interface = gr.Interface(
     fn=image_fn,
     inputs=[
-    gr.Image(type="numpy", label="Input Image"),
-    gr.Dropdown(
+    gr.inputs.Image(type="pil", label="Input Image"),
+    gr.inputs.Dropdown(
         choices=[
             "Aalaa/Yolov7_Visual_Pollution_Detection",
         ],
@@ -53,7 +53,7 @@ image_interface = gr.Interface(
     #gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"),
     #gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold")
 ],
-    outputs=gr.Image(type="filepath", label="Output Image"),
+    outputs=gr.outputs.Image(type="filepath", label="Output Image"),
     
     examples=[['image1.jpg', 'Aalaa/Yolov7_Visual_Pollution_Detection', 640, 0.25, 0.45]],
     cache_examples=True,