Update app.py

app.py

@@ -157,7 +157,7 @@ def segment_image(img,prompt_mode, categoryname, custom_category, expressiong, r
             if  categoryname =="COCO-80":
                 batch_category_name = coco_class_name
             elif categoryname =="OBJ365":
-                batch_category_name = obj365_class_name
+                batch_category_name = OBJ365_class_names
             elif categoryname =="Custom-List":
                 batch_category_name = custom_category.split(',')
             else:
@@ -450,7 +450,7 @@ with gr.Blocks() as demo:
                                 'For interactive segmentation:<br />\
                                     1.Draw points, boxes, or scribbles on the canvas for multiclass segmentation; use separate layers for different objects, adding layers with a "+" sign.<br />\
                                     2.Point mode accepts a single point only; multiple points default to the centroid, so use boxes or scribbles for larger objects.<br />\
-                                    3.After drawing, click green "√" to preview the prompt visualization; the segmentation mask follows the chosen prompt colors.'
+                                    3.After drawing, click green "√" on the right side of the image to preview the prompt visualization; the segmentation mask follows the chosen prompt colors.'
                                 )
                         with gr.Accordion("Text based detection usage",open=False):
                             gr.Markdown(
@@ -470,7 +470,7 @@ with gr.Blocks() as demo:
                     results_select = gr.CheckboxGroup(["box", "mask", "name", "score", "expression"], value=["box", "mask", "name", "score"], label="Shown Results", info="The results shown on image")
                     num_inst_select = gr.Slider(1, 50, value=15, step=1, label="Num of topK instances for category based detection", info="Choose between 1 and 50 for better visualization")
                     threshold_select = gr.Slider(0, 1, value=0.2, label="Confidence Threshold", info="Choose threshold ")
-                    mask_image_mix_ration = gr.Slider(0, 1, value=0.65, label="Image Brightness Ratio", info="Brightness between image and colored masks ")
+                    mask_image_mix_ration = gr.Slider(0, 1, value=0.45, label="Image Brightness Ratio", info="Brightness between image and colored masks ")