app update

README.md

@@ -4,9 +4,9 @@ emoji: 🚀
 colorFrom: purple
 colorTo: yellow
 sdk: gradio
-sdk_version: 3.0.1
+sdk_version: 3.0.2
 app_file: app.py
-pinned: false
+pinned: true
 license: gpl-3.0
 ---
 

app.py

@@ -317,16 +317,15 @@ def main(args):
     model_cls_name_cp = model_cls_name.copy() # class name
 
     # ------------------- Input Components -------------------
-    inputs_img = gr.inputs.Image(image_mode="RGB", source=source, tool=img_tool, type="pil", label="original image")
-    inputs_device = gr.inputs.Radio(choices=["cuda:0", "cpu"], default=device, label="device")
-
-    inputs_model = gr.inputs.Dropdown(choices=model_names, default=model_name, type="value", label="model")
-    inputs_size = gr.inputs.Radio(choices=[320, 640, 1280], default=inference_size, label="inference size")
-    input_conf = gr.inputs.Slider(0, 1, step=slider_step, default=nms_conf, label="confidence threshold")
-    inputs_iou = gr.inputs.Slider(0, 1, step=slider_step, default=nms_iou, label="IoU threshold")
-    inputs_maxnum = gr.inputs.Textbox(lines=1, placeholder="Maximum number of detections", default=max_detnum, label="Maximum number of detections")
-    inputs_clsName = gr.inputs.CheckboxGroup(choices=model_cls_name, default=model_cls_name, type="index", label="category")
-    inputs_opt = gr.inputs.CheckboxGroup(choices=["label", "pdf", "json"],
+    inputs_img = gr.Image(image_mode="RGB", source=source, tool=img_tool, type="pil", label="original image")
+    inputs_device = gr.Radio(choices=["cuda:0", "cpu"], default=device, label="device")
+    inputs_model = gr.Dropdown(choices=model_names, default=model_name, type="value", label="model")
+    inputs_size = gr.Radio(choices=[320, 640, 1280], default=inference_size, label="inference size")
+    input_conf = gr.Slider(0, 1, step=slider_step, default=nms_conf, label="confidence threshold")
+    inputs_iou = gr.Slider(0, 1, step=slider_step, default=nms_iou, label="IoU threshold")
+    inputs_maxnum = gr.Textbox(lines=1, placeholder="Maximum number of detections", default=max_detnum, label="Maximum number of detections")
+    inputs_clsName = gr.CheckboxGroup(choices=model_cls_name, default=model_cls_name, type="index", label="category")
+    inputs_opt = gr.CheckboxGroup(choices=["label", "pdf", "json"],
                                          default=["label", "pdf"],
                                          type="value",
                                          label="operate")
@@ -345,12 +344,12 @@ def main(args):
     ]
 
     # Output parameters
-    outputs_img = gr.outputs.Image(type="pil", label="Detection image")
-    outputs_json = gr.outputs.JSON(label="Detection information")
-    outputs_pdf = gr.outputs.File(label="Download test report")
-    outputs_df = gr.outputs.Dataframe(max_rows=5, overflow_row_behaviour="paginate", type="pandas", label="List of detection information")
-    outputs_objSize = gr.outputs.Label(label="Object size ratio statistics")
-    outputs_clsSize = gr.outputs.Label(label="Category detection proportion statistics")
+    outputs_img = gr.Image(type="pil", label="Detection image")
+    outputs_json = gr.JSON(label="Detection information")
+    outputs_pdf = gr.File(label="Download test report")
+    outputs_df = gr.Dataframe(max_rows=5, overflow_row_behaviour="paginate", type="pandas", label="List of detection information")
+    outputs_objSize = gr.Label(label="Object size ratio statistics")
+    outputs_clsSize = gr.Label(label="Category detection proportion statistics")
 
     outputs = [outputs_img, outputs_objSize, outputs_clsSize, outputs_json, outputs_pdf, outputs_df]
 
@@ -412,8 +411,8 @@ def main(args):
         description=description,
         article="",
         # examples=examples,
-        theme="seafoam",
-        flagging_dir="run", # output directory
+        # theme="seafoam",
+        # flagging_dir="run", # output directory
     ).launch(
         inbrowser=True, # Automatically open default browser
         show_tips=True, # Automatically display the latest features of gradio