updating to checkpoint v2

app.py

@@ -195,7 +195,7 @@ with gr.Blocks(title='Shark Patrol',theme=gr.themes.Soft(),live=True,) as demo:
         with gr.Row():
             video_example = gr.Video(source='upload',include_audio=False,stream=True)
         with gr.Row():
-            paths = sorted(pathlib.Path('videos_example/').rglob('*rgb.mp4'))
+            paths = sorted(pathlib.Path('videos_example/').rglob('*rgb.mp4'))[:8]
             example_preds = gr.Dataset(components=[video_example],
                                     samples=[[path.as_posix()]
                                              for path in paths])
@@ -212,16 +212,17 @@ with gr.Blocks(title='Shark Patrol',theme=gr.themes.Soft(),live=True,) as demo:
         
         video_button = gr.Button("Analyze your Video")
         with gr.Row():
-            paths = sorted(pathlib.Path('videos_example/').rglob('*.mp4'))
+            paths = sorted(pathlib.Path('videos_example/raw_videos/').rglob('*.mp4'))
+            print(paths)
             example_images = gr.Dataset(components=[video_input],
                                     samples=[[path.as_posix()]
-                                             for path in paths if 'raw_videos' not in str(path)])
-
-    video_button.click(analyze_video_parallel, inputs=video_input, outputs=video_output)
-
-    example_images.click(fn=set_example_image,
+                                             for path in paths])
+            example_images.click(fn=set_example_image,
                          inputs=example_images,
                          outputs=video_input)
+    video_button.click(analyze_video_parallel, inputs=video_input, outputs=video_output)
+
+   
 
 demo.queue()
 #if os.getenv('SYSTEM') == 'spaces':

inference.py

@@ -19,22 +19,22 @@ import concurrent.futures
 import threading
 
 
-classes= ['Beach',
+
+classes= [ 'Beach', 
  'Sea',
  'Wave',
  'Rock',
  'Breaking wave',
  'Reflection of the sea',
  'Foam',
- 'Algae',
- 'Vegetation',
+ 'Algae', 
+ 'Vegetation', 
  'Watermark',
  'Bird',
- 'Ship',
- 'Boat',
- 'Car',
+ 'Ship', 
+ 'Boat', 
+ 'Car', 
  'Kayak',
- "Shark's line",
  'Dock',
  'Dog',
  'Unidentifiable shade',
@@ -44,33 +44,37 @@ classes= ['Beach',
  'Surfer shadow',
  'Shark shadow',
  'Surfboard shadow',
+ 'Turtle',
  'Crocodile',
  'Sea cow',
  'Stingray',
  'Person',
- 'ocean',
- 'Surfer',
+ 'Surf table',
  'Surfer',
+ 'Seal',
  'Fish',
  'Killer whale',
  'Whale',
  'Dolphin',
  'Miscellaneous',
- 'Unidentifiable shark',
+ "Shark's line",
+ 'Unidentifiable shark', 
  'Carpet shark',
  'Dusty shark',
  'Blue shark',
  'Great white shark',
- 'Copper shark',
- 'Nurse shark',
- 'Silky shark',
- 'Leopard shark',
- 'Shortfin mako shark',
- 'Hammerhead shark',
- 'Oceanic whitetip shark',
- 'Blacktip shark',
- 'Tiger shark',
- 'Bull shark']*3
+ 'Copper shark', 
+ 'Nurse shark', 
+ 'Silky shark', 
+ 'Leopard shark', 
+ 'Shortfin mako shark', 
+ 'Hammerhead shark', 
+ 'Oceanic whitetip shark', 
+ 'Blacktip shark', 
+ 'Tiger shark', 
+ 'Bull shark']
+
+classes +=['None']*50
 
 
 
@@ -89,7 +93,7 @@ snapshot_download(repo_id=REPO_ID, token= os.environ.get('SHARK_MODEL'),local_di
 config_file ='model/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic.py'
 #'/content/mmdetection/configs/panoptic_fpn/panoptic-fpn_r50_fpn_ms-3x_coco.py'
 # Setup a checkpoint file to load
-checkpoint_file ='model/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic/checkpoint.pth'
+checkpoint_file ='model/mask2former_swin-t-p4-w7-224_8xb2-lsj-50e_coco-panoptic/checkpoint_v2.pth'
 # '/content/drive/MyDrive/Algorithms/weights/shark_panoptic_weights_16_4_23/panoptic-fpn_r50_fpn_ms-3x_coco/epoch_36.pth'
 
 # register all modules in mmdet into the registries