Merge branch 'master' of https://github.com/Microsoft/VoTT

README.md

@@ -32,11 +32,11 @@ The tool supports the following **features**:
 
  ### Installing CNTK with the FRCNN Prerequisites for Reviewing Model
 
-*Please note that installation of **CNTK and FAST-RCNN dependencies** are **optional for tagging** and are **only required for CNTK model review and training**.*
+*Please note that installation of **CNTK and FASTER-RCNN dependencies** are **optional for tagging** and are **only required for CNTK model review and training**.*
 
 1. Install [CNTK](https://github.com/Microsoft/CNTK/wiki/Setup-CNTK-on-your-machine) (*Note: currently the tool only supports the full installation method (non pip) of CNTK*).
 
-2. Follow the setup instructions of the [CNTK Fast-RCNN tutorial](https://github.com/Microsoft/CNTK/wiki/Object-Detection-using-Fast-R-CNN#setup) (*Note: Fast-RCNN currently only supports Linux python version 3.4 and not 3.5*).
+2. Follow the setup instructions of the [CNTK Faster-RCNN tutorial](https://docs.microsoft.com/en-us/cognitive-toolkit/object-detection-using-faster-r-cnn#setup) (*Note: Faster-RCNN currently only supports Linux python version 3.4 and not 3.5*).
 
 3. Configure `CNTK-Config.json` (which resides in the '\resources\app' directory of the tagging tool) with the following properties to enable the model review feature:
 
@@ -162,18 +162,8 @@ The tool supports the following **features**:
 ---
 ## Reviewing and Improving an Object Detection Model
 
- 1. Train model with [Object Detection using FastRCNN](https://github.com/Microsoft/CNTK/wiki/Object-Detection-using-Fast-R-CNN#train-on-your-own-data)<br> *Note: the data is already in CNTK format, so you do not have to run `C1_DrawBboxesOnImages.py` or `C2_AssignLabelsToBboxes.py`*
- 2. Since CNTK does not embed the names of the classes in the model, on default, the module returns non descriptive names for the classes, e.g. "class_1", "class_2".Place a JSON file named "model.json" in the same directory of the Fast-RCNN model file with the the correct tag labels. Format the json file as follows with your own class names:
-   ```json
-   {
-       "classes" : {
-           "background" : 0,
-           "human" : 1,
-     "cat" : 2,
-     "dog" : 3
-       }
-   }
-   ```
+ 1. Train model with [Object Detection using FasterRCNN](https://docs.microsoft.com/en-us/cognitive-toolkit/object-detection-using-faster-r-cnn#run-faster-r-cnn-on-your-own-data)<br> 
+ 2. Since CNTK does not embed the names of the classes in the model, on default, the module returns non descriptive names for the classes, e.g. "class_1", "class_2". To resolve this copy the class_map.txt file generated by the FASTER-RCNN tutorial to the same directory that contains your model.   
 
  3. Load a new asset that the model has not been trained on
  4. Configure a new or load a previous tagging job 
@@ -191,6 +181,9 @@ In the latest release we provide support for [Export and Review formats](https:/
 ## Upcoming Features 
 
 - Tagging project management
+- Altenative Tracking algorithms such as optical flow.
+- Classification Labeling Support
+- Segmentation Annoatation support.
 
 -----------
 

package.json

@@ -21,7 +21,7 @@
   },
   "dependencies": {
     "async": "^2.1.5",
-    "cntk-fastrcnn": "^0.2.6",
+    "cntk-fastercnn": "^0.1.1",
     "electron": "^1.4.1",
     "electron-window-state": "^4.0.2",
     "remote": "^0.2.6",