Merge remote-tracking branch 'origin/dev'

Author: sadda

README.md

@@ -147,8 +147,8 @@ import numpy as np
 from wildlife_tools.inference import KnnClassifier
 
 classifier = KnnClassifier(k=1, database_labels=dataset_database.labels_string)
-predictions = classifier(similarity['cosine'])
-accuracy = np.mean(dataset_database.labels_string == predictions)
+predictions = classifier(similarity)
+accuracy = np.mean(dataset_query.labels_string == predictions)
 ```
 
 ## Citation

baselines/inference/MegaDescriptor-B-224.ipynb

@@ -96,7 +96,7 @@
     "\n",
     "    matcher = CosineSimilarity()\n",
     "    similarity = matcher(query=extractor(query), database=extractor(database))\n",
-    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity['cosine'])\n",
+    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity)\n",
     "    \n",
     "    acc = sum(preds == query.labels_string) / len(preds)\n",
     "    print(name, acc)\n",

baselines/inference/MegaDescriptor-L-224.ipynb

@@ -535,7 +535,7 @@
     "\n",
     "    matcher = CosineSimilarity()\n",
     "    similarity = matcher(query=extractor(query), database=extractor(database))\n",
-    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity['cosine'])\n",
+    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity)\n",
     "    \n",
     "    acc = sum(preds == query.labels_string) / len(preds)\n",
     "    print(name, acc)\n",

baselines/inference/MegaDescriptor-L-384.ipynb

@@ -541,7 +541,7 @@
     "\n",
     "    matcher = CosineSimilarity()\n",
     "    similarity = matcher(query=extractor(query), database=extractor(database))\n",
-    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity['cosine'])\n",
+    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity)\n",
     "\n",
     "    acc = sum(preds == query.labels_string) / len(preds)\n",
     "    print(name, acc)\n",

baselines/inference/MegaDescriptor-S-224.ipynb

@@ -533,7 +533,7 @@
     "\n",
     "    matcher = CosineSimilarity()\n",
     "    similarity = matcher(query=extractor(query), database=extractor(database))\n",
-    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity['cosine'])\n",
+    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity)\n",
     "    \n",
     "    acc = sum(preds == query.labels_string) / len(preds)\n",
     "    print(name, acc)\n",

baselines/inference/MegaDescriptor-T-224.ipynb

@@ -532,7 +532,7 @@
     "\n",
     "    matcher = CosineSimilarity()\n",
     "    similarity = matcher(query=extractor(query), database=extractor(database))\n",
-    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity['cosine'])\n",
+    "    preds = KnnClassifier(k=1, database_labels=database.labels_string)(similarity)\n",
     "    \n",
     "    acc = sum(preds == query.labels_string) / len(preds)\n",
     "    print(name, acc)\n",

docs/index.md

@@ -153,8 +153,8 @@ import numpy as np
 from wildlife_tools.inference import KnnClassifier
 
 classifier = KnnClassifier(k=1, database_labels=dataset_database.labels_string)
-predictions = classifier(similarity['cosine'])
-accuracy = np.mean(dataset_database.labels_string == predictions)
+predictions = classifier(similarity)
+accuracy = np.mean(dataset_query.labels_string == predictions)
 ```
 
 ## Citation