New model layout, deleted a few redundant images

app.py

@@ -53,9 +53,11 @@ NAME_TO_CLASS_IDX = {name: idx for idx, name in enumerate(CLASS_NAMES)}
 
 # Model information from models.txt
 MODEL_INFO = [
+    {"org": "Facebook", "name": "PE-Core", "logo": "logos/meta.png"},
     {"org": "Google", "name": "SigLIP2", "logo": "logos/google.png"},
     {"org": "OpenAI", "name": "CLIPViT-L", "logo": "logos/openai.png"},
-    {"org": "Imageomics", "name": "BioCLIP", "logo": "logos/imageomics.png"}
+    {"org": "Imageomics", "name": "BioCLIP", "logo": "logos/imageomics.png"},
+    {"org": "LAION", "name": "CLIP-L", "logo": "logos/laion.png"}
 ]
 
 DEMO_LEARNING_RATE = 0.05 # don't use default; use something more fun
@@ -205,7 +207,7 @@ def add_logo_to_x_axis(ax, x_pos, logo_path, model_name, height_px=35):
         imagebox = OffsetImage(img, zoom=zoom)
 
         # Position logo to the left of the x-tick
-        logo_offset = -0.2  # Adjust this to move logo left/right relative to tick
+        logo_offset = -0.28  # Adjust this to move logo left/right relative to tick
         y_offset = -0.08
         ab = AnnotationBbox(imagebox, (x_pos + logo_offset, y_offset),
                            xycoords=('data', 'axes fraction'), frameon=False)
@@ -333,7 +335,7 @@ def create_probability_chart():
     else:
         probs_tensor = coda_selector.get_pbest()
         probabilities = probs_tensor.detach().cpu().numpy().flatten()
-        model_labels = ["   " + info['name'] for info in MODEL_INFO[:len(probabilities)]]
+        model_labels = [" "*(3 + len(info['name'])//4) + info['name'] for info in MODEL_INFO[:len(probabilities)]]
 
     # Find the index of the highest probability
     best_idx = np.argmax(probabilities)
@@ -397,7 +399,9 @@ def create_accuracy_chart():
         confusion_matrices.append(conf_matrix)
 
     # Create subplots for each model
-    fig, axes = plt.subplots(1, num_models, figsize=(8, 2.8), dpi=150)
+    # Adjust width based on number of models (2.4 inches per model works well)
+    fig_width = num_models * 2.4
+    fig, axes = plt.subplots(1, num_models, figsize=(fig_width, 2.8), dpi=150)
     if num_models == 1:
         axes = [axes]
 

images.txt

@@ -1,5 +1,4 @@
 92ef0bc6-21bc-11ea-a13a-137349068a90.jpg
-89e3a9c4-21bc-11ea-a13a-137349068a90.jpg
 902e0068-21bc-11ea-a13a-137349068a90.jpg
 8bbbf896-21bc-11ea-a13a-137349068a90.jpg
 8caf22be-21bc-11ea-a13a-137349068a90.jpg
@@ -188,11 +187,8 @@
 8f4dd7f4-21bc-11ea-a13a-137349068a90.jpg
 8f88c6e8-21bc-11ea-a13a-137349068a90.jpg
 8aaabb04-21bc-11ea-a13a-137349068a90.jpg
-8768fa28-21bc-11ea-a13a-137349068a90.jpg
-9505e7fe-21bc-11ea-a13a-137349068a90.jpg
 8f337b16-21bc-11ea-a13a-137349068a90.jpg
 8f20690e-21bc-11ea-a13a-137349068a90.jpg
-92789e50-21bc-11ea-a13a-137349068a90.jpg
 8bf1327c-21bc-11ea-a13a-137349068a90.jpg
 8c7ef620-21bc-11ea-a13a-137349068a90.jpg
 92b99fb8-21bc-11ea-a13a-137349068a90.jpg
@@ -886,7 +882,6 @@
 8a9d3d26-21bc-11ea-a13a-137349068a90.jpg
 91bea306-21bc-11ea-a13a-137349068a90.jpg
 98027508-21bc-11ea-a13a-137349068a90.jpg
-93ca69e6-21bc-11ea-a13a-137349068a90.jpg
 8a31dad6-21bc-11ea-a13a-137349068a90.jpg
 8f803276-21bc-11ea-a13a-137349068a90.jpg
 92ae2b6a-21bc-11ea-a13a-137349068a90.jpg
@@ -1034,7 +1029,6 @@
 949d098c-21bc-11ea-a13a-137349068a90.jpg
 8fd985d8-21bc-11ea-a13a-137349068a90.jpg
 91785bee-21bc-11ea-a13a-137349068a90.jpg
-8d76206c-21bc-11ea-a13a-137349068a90.jpg
 88e4a06e-21bc-11ea-a13a-137349068a90.jpg
 8c0f47a8-21bc-11ea-a13a-137349068a90.jpg
 929f0432-21bc-11ea-a13a-137349068a90.jpg

iwildcam_demo.pt

@@ -1,3 +1,3 @@
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-size 128467
+oid sha256:759d1ee32793a1f160d5f6a8ca75f71c7ce9f9cfc3889e59bdf395e729b49061
+size 127891

iwildcam_demo_annotations.json

@@ -11,17 +11,6 @@
       "file_name": "92ef0bc6-21bc-11ea-a13a-137349068a90.jpg",
       "seq_frame_num": 0
     },
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-      "location": 372,
-      "datetime": "2015-02-11 01:13:30.000",
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-      "seq_id": "302f54e0-7d42-11eb-8fb5-0242ac1c0002",
-      "width": 1920,
-      "height": 1080,
-      "file_name": "89e3a9c4-21bc-11ea-a13a-137349068a90.jpg",
-      "seq_frame_num": 1
-    },
     {
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       "location": 372,
@@ -2166,28 +2155,6 @@
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       "seq_frame_num": 4
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-    {
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-      "datetime": "2013-02-03 01:47:56.000",
-      "id": "8768fa28-21bc-11ea-a13a-137349068a90",
-      "seq_id": "302607f0-7d42-11eb-8fb5-0242ac1c0002",
-      "width": 1920,
-      "height": 1080,
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-      "datetime": "2013-02-03 01:48:26.000",
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-      "seq_id": "302607f0-7d42-11eb-8fb5-0242ac1c0002",
-      "width": 1920,
-      "height": 1080,
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@@ -2210,17 +2177,6 @@
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-    {
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-      "datetime": "2013-02-03 01:49:12.000",
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-      "seq_id": "302607f0-7d42-11eb-8fb5-0242ac1c0002",
-      "width": 1920,
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@@ -10111,17 +10067,6 @@
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       "seq_frame_num": 0
     },
-    {
-      "seq_num_frames": 6,
-      "location": 261,
-      "datetime": "2013-01-22 23:58:11.000",
-      "id": "93ca69e6-21bc-11ea-a13a-137349068a90",
-      "seq_id": "980276ac-21bc-11ea-a13a-137349068a90",
-      "width": 1920,
-      "height": 1080,
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@@ -11793,17 +11738,6 @@
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@@ -17872,16 +17806,6 @@
       "image_id": "8aaabb04-21bc-11ea-a13a-137349068a90",
       "category_id": 101
     },
-    {
-      "id": "9aa54646-21bc-11ea-a13a-137349068a90",
-      "image_id": "8768fa28-21bc-11ea-a13a-137349068a90",
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-      "image_id": "9505e7fe-21bc-11ea-a13a-137349068a90",
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       "id": "9e29cd1e-21bc-11ea-a13a-137349068a90",
       "image_id": "8f337b16-21bc-11ea-a13a-137349068a90",
@@ -17892,16 +17816,6 @@
       "image_id": "8f20690e-21bc-11ea-a13a-137349068a90",
       "category_id": 101
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-    {
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-      "image_id": "92789e50-21bc-11ea-a13a-137349068a90",
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@@ -18092,11 +18006,6 @@
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@@ -18717,11 +18626,6 @@
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       "image_id": "902e0068-21bc-11ea-a13a-137349068a90",

iwildcam_demo_labels.pt

@@ -1,3 +1,3 @@
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 size 11780