Update demo.py

demo.py

@@ -1,9 +1,18 @@
-from metaseg import SegAutoMaskPredictor, SegManualMaskPredictor, SahiAutoSegmentation, sahi_sliced_predict
+from metaseg import (
+    SahiAutoSegmentation,
+    SegAutoMaskPredictor,
+    SegManualMaskPredictor,
+    sahi_sliced_predict,
+)
 
 # For image
 
-def automask_image_app(image_path, model_type, points_per_side, points_per_batch, min_area):
+
+def automask_image_app(
+    image_path, model_type, points_per_side, points_per_batch, min_area
+):
     SegAutoMaskPredictor().image_predict(
+        
         source=image_path,
         model_type=model_type,  # vit_l, vit_h, vit_b
         points_per_side=points_per_side,
@@ -18,7 +27,10 @@ def automask_image_app(image_path, model_type, points_per_side, points_per_batch
 
 # For video
 
-def automask_video_app(video_path, model_type, points_per_side, points_per_batch, min_area):
+
+def automask_video_app(
+    video_path, model_type, points_per_side, points_per_batch, min_area
+):
     SegAutoMaskPredictor().video_predict(
         source=video_path,
         model_type=model_type,  # vit_l, vit_h, vit_b
@@ -32,7 +44,16 @@ def automask_video_app(video_path, model_type, points_per_side, points_per_batch
 
 # For manuel box and point selection
 
-def manual_app(image_path, model_type, input_point, input_label, input_box, multimask_output, random_color):
+
+def manual_app(
+    image_path,
+    model_type,
+    input_point,
+    input_label,
+    input_box,
+    multimask_output,
+    random_color,
+):
     SegManualMaskPredictor().image_predict(
         source=image_path,
         model_type=model_type,  # vit_l, vit_h, vit_b
@@ -50,6 +71,7 @@ def manual_app(image_path, model_type, input_point, input_label, input_box, mult
 
 # For sahi sliced prediction
 
+
 def sahi_autoseg_app(
     image_path,
     sam_model_type,
@@ -64,7 +86,8 @@ def sahi_autoseg_app(
 ):
     boxes = sahi_sliced_predict(
         image_path=image_path,
-        detection_model_type=detection_model_type,  # yolov8, detectron2, mmdetection, torchvision
+        # yolov8, detectron2, mmdetection, torchvision
+        detection_model_type=detection_model_type,
         detection_model_path=detection_model_path,
         conf_th=conf_th,
         image_size=image_size,
@@ -74,7 +97,7 @@ def sahi_autoseg_app(
         overlap_width_ratio=overlap_width_ratio,
     )
 
-    SahiAutoSegmentation().predict(
+    SahiAutoSegmentation().image_predict(
         source=image_path,
         model_type=sam_model_type,
         input_box=boxes,
@@ -83,5 +106,5 @@ def sahi_autoseg_app(
         show=False,
         save=True,
     )
-    
+
     return "output.png"