Hey there, amazing tool, thanks for sharing!

I wonder if it is possible to draw the class label along with the bounding box for each prediction (possibly with the possibility of turning on/off the feature)

Actually, this bit of the code is supposed to do that, is that the case this works only for tf2 models? https://github.com/datature/portal/blob/a972880183c3465f1851a6b360a87c47691495c5/src/engine/server/utilities/prediction_utilities.py#L616-L631

After running requirements.txt:

ERROR: Could not find a version that satisfies the requirement datature-hub==0.2.0 (from versions: none) ERROR: No matching distribution found for datature-hub==0.2.0

When I tried installing datature-hub via pip install datature-hub https://pypi.org/project/datature-hub/ error =

ERROR: Could not find a version that satisfies the requirement datature-hub (from versions: none)
ERROR: No matching distribution found for datature-hub

HotKey B and the menu item bulk analysis button will invoke bulkAnalysis() method which goes through the entire assetList to get inference for each of the asset.

Under the Advance Settings, the User is able to choose if they want the bulk analysis to include Image Only, Video Only or Image and Video

Includes end bulk analysis and end video prediction. Does not work for ending image prediction

Overall changes made:

• Thumbnail of the pictures that has been cached has a bookmark icon wrapped with a ToolTip info "Inference is Cached by Model"
• Each time a picture with cached predictions is selected, it will silently call the prediction route. (Remove the progress bar but the spinner on the annotation menu still remains)

How the changes are made:

1. Add a isCached field in the AssetAPIObject type --> which will be used to check if the asset needs a bookmark icon on its thumbnail
2. Add a cachedList array which will be called and updated each time the imagebar needs to be updated (aka, refer below)

• ComponentDidMount
• ComponentDidUpdate (when the global loadedModel is updated)
• getInference (when a prediction is being called)

Change the name from annotator to portal Bash jobs all exits when an error occurs For the setup bash files, added a condition that checks for the necessary files that needs to be transferred to portal-build first Pyinstaller error for macos change python3 portal-build/portal.py to python3 portal.py

Mac:

git clone https://github.com/datature/portal
chmod u+x ./setup-virtualenv.sh && ./setup-virtualenv.sh
. portal-build/.venv/bin/activate
python3 portal-build/portal.py (additional flags include --electron and --gpu)

Win:

git clone https://github.com/datature/portal
setup-virtualenv.sh
portal-build\.venv\Scripts\activate
python portal-build\portal.py  (additional flags include --electron and --gpu)

Additional Stuff changed:

1. Toaster logic (On browser mode, the blue toaster will stay forever until it detects the backend)
2. Set a global isConnected state
3. Disable inference buttons when there is no loaded model. On hover, a tooltip info will appear
4. OnComponentDidMount, the model component will call the get model list api until it gets a postive ans. During the wait, the model button is in skeleton mode
5. GPU feature to request for a restart

1. Changes to the Cache saving and loading methods

• Instead of saving the entire model class object, the model class is deconstructed on save, and reconstructed on load

2. Changes to loaded model location in the code

• Loaded models are now fully integrated into their respective model class
• Docstrings for this change has been updated.

3. Added new autosave toggling feature

• Introduced new variable var/cache.var.
• Enabling/Disabling autosave will update the var/cache.var flag.
• Whenever Portal starts, autosave will be set based on the value in var/cache.var.
• Autosave is defaulted to false on first start.
• Enabling autosave will immediately create the portalCache file.
• Disabling autosave will immediately delete the portalCache file.

4. Created support for Hosted Deployment into Portal

• Added new tab in model registration interface called "Datature API (Coming Soon)"
• (The tab is currently greyed out)
• Upon clicking the tab users can enter Name, API Link, and Project Secret to register their API as a model.
• Subsequent Steps to load/make predictions will not be different from previous methods.

5. Introduced option for certain model types to be saved in cache.

• With the introduction of Datature API, saving the credentials (API link and project secret) could be a security breach.
• This new option allows newly created custom model types to specify if they want their credentials to be saved in cache.
• All registered models that have the save_in_cache flag turned off will not have their credentials saved in cache.
• Image predictions tagged to this model will still be saved in cache nonetheless (The registered model key used for indexing has already been hashed).

6. Changed default video frame sampling rate from 20 to 1.
7. Moved and renamed use_gpu from cache/use_gpu to var/gpu.var.
8. hub_models, var and cache folders will no longer be persistent (removed from github), and will instead be dynamically created upon first startup.

Changes

• add new package recharts
• add new button for visualizing the number of recognized objects over time
• add feature for video seeking on the graph

Success Criteria

• [x] Render timeline graph
• [x] Timeline graph shows composition of objects (each frame is one datapoint)
• [x] Selecting the graph shows you the number of particular objects on a given frame
• [x] On selection of datapoint of a video, the video will seek to the timepoint

Screenshots

Describe the bug Portal runtime is unresponsive when launching the application.

To Reproduce Running this build: https://github.com/datature/portal/releases/tag/v0.5.5 On MacOs

Uncaught (in promise) Error: Network Error
    at e.exports (835-91f7fb22de8eba0dd168.js:1)
    at XMLHttpRequest.p.onerror (835-91f7fb22de8eba0dd168.js:1)
localhost:9449/api/project/assets:1 
Failed to load resource: net::ERR_CONNECTION_REFUSED
835-91f7fb22de8eba0dd168.js:1 
Uncaught (in promise) Error: Network Error
    at e.exports (835-91f7fb22de8eba0dd168.js:1)
    at XMLHttpRequest.p.onerror (835-91f7fb22de8eba0dd168.js:1)```

Ask your question and elaborate its context I see you mentioning TensorFlow models, but does Portal support TensorFlow.js? If so that would be huge for me.

Additional context If you support TensorFlow.js I'd love to do a blog post and video demo to put on Twitter!

Hello everyone, thanks a lot for developing this application. Looks super useful and would make all our lives much easier. I have installed your portal application for windows provided in the link (Portal-0.5.0-windows.exe). After installing, I am facing two errors:

1. I am trying to load yolov3. I have downloaded the model using the link given in the readme. Now, I am trying to load the model in the + but I get the error stating Failed to register model. The model file directory is as follows:

└── YOLOv3 ImageNet
    ├──  __MACOSX
    └── YOLOv3 ImageNet
          ├─ coco (names file)
          ├─ yolov3 (CFG file)
          └─ yolov3 (WEIGHTS file)

2. I am also continuously getting a prompt error saying Portal runtime is unresponsive. (Also can be seen in the snap below)