docs: fixes broken links (#8)

docs/docs/metrics/geometric.md

@@ -21,57 +21,57 @@ Ranks annotations by how likely they are to represent the same object.
 > [Jaccard similarity coefficient](https://en.wikipedia.org/wiki/Jaccard_index)
 > is used to measure closeness of two annotations.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/annotation_duplicates.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/annotation_duplicates.py)
 
 ## Annotation closeness to image borders
 
 This metric ranks annotations by how close they are to image borders.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/image_border_closeness.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/image_border_closeness.py)
 
 ## Detect Occlusion in Video
 
 This metric collects information related to object size and aspect ratio for each track
 and find outliers among them.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/occlusion_detection_video.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/occlusion_detection_video.py)
 
 ## Frame object density
 
 Computes the percentage of image area that's occupied by objects.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/object_size.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/object_size.py)
 
 ## Object Area - Absolute
 
 Computes object area in amount of pixels.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/object_size.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/object_size.py)
 
 ## Object Area - Relative
 
 Computes object area as a percentage of total image area.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/object_size.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/object_size.py)
 
 ## Object Aspect Ratio
 
 Computes aspect ratios ($width/height$) of objects.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/object_size.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/object_size.py)
 
 ## Polygon Shape Similarity
 
 This metric ranks objects by how similar they are to their instances in previous frames
 based on [Hu moments](https://en.wikipedia.org/wiki/Image_moment). The more an object's shape changes,
 the lower its score will be.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/hu_temporal.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/hu_temporal.py)
 
 ## Shape outlier detection
 
 Computes the Euclidean distance between the polygons'
 [Hu moments](https://en.wikipedia.org/wiki/Image_moment) for each class and
 the prototypical class moments.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/geometric/hu_static.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/geometric/hu_static.py)

docs/docs/metrics/heuristic.md

@@ -23,21 +23,21 @@ This metric ranks images by their area (width\*height).
 
 Area is computed as the product of image width and image height.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)
 
 ## Aspect Ratio
 
 This metric ranks images by their aspect ratio (width/height).
 
 Aspect ratio is computed as the ratio of image width to image height.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)
 
 ## Blue Values
 
 This metric ranks images by how much blue is present in the image.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)
 
 ## Blur
 
@@ -51,29 +51,29 @@ image. Note that this is $1 - \text{sharpness}$.
 score = 1 - cv2.Laplacian(image, cv2.CV_64F).var()
 ```
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)
 
 ## Brightness
 
 This metric ranks images by their brightness.
 
 Brightness is computed as the average (normalized) pixel value across each image.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)
 
 ## Contrast
 
 This metric ranks images by their contrast.
 
 Contrast is computed as the standard deviation of the pixel values.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)
 
 ## Green Values
 
 This metric Ranks images by how much blue is present in the image.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)
 
 ## Inconsistent Object Classification and Track IDs
 
@@ -115,7 +115,7 @@ track-ids, they will be flagged as potential inconsistencies in tracks.
 
 `Cat:2` will be flagged as potentially having a broken track, because track ids `1` and `2` doesn't match.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/high_iou_changing_classes.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/high_iou_changing_classes.py)
 
 ## Missing Objects and Broken Tracks
 
@@ -162,19 +162,19 @@ hash, they will be flagged as a potentially broken track.
 
 `CAT:2` will be marked as potentially having a wrong track id.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/missing_objects_and_wrong_tracks.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/missing_objects_and_wrong_tracks.py)
 
 ## Object Count
 
 Counts number of objects in the image.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/object_counting.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/object_counting.py)
 
 ## Red Values
 
 This metric ranks images by how much red is present in the image.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)
 
 ## Sharpness
 
@@ -188,4 +188,4 @@ image.
 score = cv2.Laplacian(image, cv2.CV_64F).var()
 ```
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/heuristic/img_features.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/heuristic/img_features.py)

docs/docs/metrics/semantic.md

@@ -12,12 +12,12 @@ Operates with the semantic information of images or individual video frames.
 This metric creates embeddings from images. Then, these embeddings are used to build
 nearest neighbor graph. Similar embeddings' classifications are compared against each other.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/semantic/img_classification_quality.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/semantic/img_classification_quality.py)
 
 ## Object Annotation Quality
 
 This metric transforms polygons into bounding boxes
 and an embedding for each bounding box is extracted. Then, these embeddings are compared
 with their neighbors. If the neighbors are annotated differently, a low score is given to it.
 
-Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/encord_active.metrics/semantic/img_object_quality.py)
+Implementation on [GitHub](https://github.com/encord-team/encord-active/blob/main/src/encord_active/lib/metrics/semantic/img_object_quality.py)