You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: Competition/ObjectDetectionSegmentation/README.md
+5-5Lines changed: 5 additions & 5 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -27,10 +27,10 @@ The goal is to improve OpenStreetMap by adding high quality baseball, soccer, te
27
27
[](https://www.youtube.com/watch?v=OOT3UIXZztE)
28
28
29
29
# Getting Started
30
-
*[demo.ipynb](./demo.ipynb) Is the easiest way to start. It shows an example of using a model pre-trained on MS COCO to segment objects in your own images.
30
+
*[demo.ipynb](demo.ipynb) Is the easiest way to start. It shows an example of using a model pre-trained on MS COCO to segment objects in your own images.
31
31
It includes code to run object detection and instance segmentation on arbitrary images.
32
32
33
-
*[Video-Demo-Mask_RCNN.ipynb](./Video-Demo-Mask_RCNN.ipynb.ipynb) Is the another easiest way to start the stream data. It shows an example of using a model pre-trained on MS COCO to segment objects from your own webcam.
33
+
*[Video-Demo-Mask_RCNN.ipynb](Video-Demo-Mask_RCNN.ipynb.ipynb) Is the another easiest way to start the stream data. It shows an example of using a model pre-trained on MS COCO to segment objects from your own webcam.
34
34
It includes code to run object detection and instance segmentation on arbitrary images.
35
35
This is an additional example which does not include in original repository. It refers from some other resources into this Jupyter notebook.
36
36
@@ -39,12 +39,12 @@ This is an additional example which does not include in original repository. It
39
39
* ([model.py](model.py), [utils.py](utils.py), [config.py](config.py)): These files contain the main Mask RCNN implementation.
40
40
41
41
42
-
*[inspect_data.ipynb](./inspect_data.ipynb). This notebook visualizes the different pre-processing steps
42
+
*[inspect_data.ipynb](inspect_data.ipynb). This notebook visualizes the different pre-processing steps
43
43
to prepare the training data.
44
44
45
-
*[inspect_model.ipynb](./inspect_model.ipynb) This notebook goes in depth into the steps performed to detect and segment objects. It provides visualizations of every step of the pipeline.
45
+
*[inspect_model.ipynb](inspect_model.ipynb) This notebook goes in depth into the steps performed to detect and segment objects. It provides visualizations of every step of the pipeline.
46
46
47
-
*[inspect_weights.ipynb](./inspect_weights.ipynb)
47
+
*[inspect_weights.ipynb](inspect_weights.ipynb)
48
48
This notebooks inspects the weights of a trained model and looks for anomalies and odd patterns.
0 commit comments