Yiming-M commited on
Commit
affc2a7
Β·
1 Parent(s): 9a7b741

2025-08-01 08:40 πŸš€

Browse files
Files changed (2) hide show
  1. README.md +1 -0
  2. app.py +5 -3
README.md CHANGED
@@ -6,6 +6,7 @@ colorTo: pink
6
  sdk: gradio
7
  sdk_version: 5.39.0
8
  app_file: app.py
 
9
  pinned: true
10
  license: mit
11
  short_description: The crowd counting model ZIP-B
 
6
  sdk: gradio
7
  sdk_version: 5.39.0
8
  app_file: app.py
9
+ suggested_hardware: t4-small
10
  pinned: true
11
  license: mit
12
  short_description: The crowd counting model ZIP-B
app.py CHANGED
@@ -20,7 +20,8 @@ mean = (0.485, 0.456, 0.406)
20
  std = (0.229, 0.224, 0.225)
21
  alpha = 0.8
22
  EPS = 1e-8
23
- device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
24
  loaded_model = None
25
  current_model_config = {"variant": None, "dataset": None, "metric": None}
26
 
@@ -432,8 +433,9 @@ def predict(image: Image.Image, variant_dataset_metric: str):
432
  # den_map = normalize_map(den_map)
433
  # complete_zero_map = normalize_map(complete_zero_map)
434
 
435
- # Apply a colormap (e.g., 'jet') to get an RGBA image
436
- colormap = cm.get_cmap("jet")
 
437
 
438
  # The colormap returns values in [0,1]. Scale to [0,255] and convert to uint8.
439
  den_map = (colormap(den_map) * 255).astype(np.uint8)
 
20
  std = (0.229, 0.224, 0.225)
21
  alpha = 0.8
22
  EPS = 1e-8
23
+ # device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
24
+ device = torch.device("cuda")
25
  loaded_model = None
26
  current_model_config = {"variant": None, "dataset": None, "metric": None}
27
 
 
433
  # den_map = normalize_map(den_map)
434
  # complete_zero_map = normalize_map(complete_zero_map)
435
 
436
+ # Apply a colormap for better visualization
437
+ # Options: 'viridis' (recommended), 'plasma', 'hot', 'inferno', 'jet'
438
+ colormap = cm.get_cmap("viridis")
439
 
440
  # The colormap returns values in [0,1]. Scale to [0,255] and convert to uint8.
441
  den_map = (colormap(den_map) * 255).astype(np.uint8)