Add sv.Classifications.from_clip data loader

supervision/classification/core.py

@@ -39,11 +39,54 @@ def __post_init__(self) -> None:
         _validate_class_ids(self.class_id, n)
         _validate_confidence(self.confidence, n)
 
+    def __len__(self) -> int:
+        """
+        Returns the number of classifications.
+        """
+        return len(self.class_id)
+
+    @classmethod
+    def from_clip(cls, clip_results) -> Classifications:
+        """
+        Creates a Classifications instance from a
+        [clip](https://github.com/openai/clip) inference result.
+
+        Args:
+            clip_results (np.ndarray): The inference result from clip model.
+
+        Returns:
+            Classifications: A new Classifications object.
+
+        Example:
+            ```python
+            >>> from PIL import Image
+            >>> import clip
+            >>> import supervision as sv
+
+            >>> model, preprocess = clip.load('ViT-B/32')
+
+            >>> image = cv2.imread(SOURCE_IMAGE_PATH)
+            >>> image = preprocess(image).unsqueeze(0)
+
+            >>> text = clip.tokenize(["a diagram", "a dog", "a cat"])
+            >>> output, _ = model(image, text)
+            >>> classifications = sv.Classifications.from_clip(output)
+            ```
+        """
+
+        confidence = clip_results.softmax(dim=-1).cpu().detach().numpy()[0]
+
+        if len(confidence) == 0:
+            return cls(class_id=np.array([]), confidence=np.array([]))
+
+        class_ids = np.arange(len(confidence))
+        return cls(class_id=class_ids, confidence=confidence)
+
     @classmethod
     def from_ultralytics(cls, ultralytics_results) -> Classifications:
         """
         Creates a Classifications instance from a
-        (https://github.com/ultralytics/ultralytics) inference result.
+        [ultralytics](https://github.com/ultralytics/ultralytics) inference result.
 
         Args:
             ultralytics_results (ultralytics.engine.results.Results):
@@ -72,7 +115,7 @@ def from_ultralytics(cls, ultralytics_results) -> Classifications:
     def from_timm(cls, timm_results) -> Classifications:
         """
         Creates a Classifications instance from a
-        timm (https://huggingface.co/docs/hub/timm) inference result.
+        [timm](https://huggingface.co/docs/hub/timm) inference result.
 
         Args:
             timm_results: The inference result from timm model.
@@ -109,7 +152,6 @@ def from_timm(cls, timm_results) -> Classifications:
             return cls(class_id=np.array([]), confidence=np.array([]))
 
         class_id = np.arange(len(confidence))
-
         return cls(class_id=class_id, confidence=confidence)
 
     def get_top_k(self, k: int) -> Tuple[np.ndarray, np.ndarray]: