Voxel51 is bringing transparency and clarity to the world's data. We build software that enables developers, scientists, and organizations to build high-quality datasets and computer vision models that power some of today's most remarkable machine learning and artificial intelligence.
Get open source FiftyOne: github.com/voxel51/fiftyone
Learn about FiftyOne Teams: voxel51.com/fiftyone-teams/
I want to work with my custom dataset. I'd like you to show me how to do it and which benefits I can get using your product. Examples, how can I refine my own data with fiftyone
Isn't the "Grid Trick" similar to using ControlNet, a type of model for controlling image diffusion models by conditioning the model with an additional input image?
How to we execute the plugin logic in the code? This doesn't seem to work: logging.info("removing approximate duplicates") operator_uri = "@jacobmarks/image_deduplication/remove_all_approximate_duplicates" params = { "sim_choices": "sim", # You may need to adjust this based on your similarity run key "threshold_value": 0.4 } # Create an invocation request request = foe.InvocationRequest(operator_uri, params=params) # Create an executor and execute the request executor = foe.Executor(requests=[request]) result = executor.trigger(operator_uri, params=params) print(result.to_json()) # logging.info(f"Found approximate duplicates: {result.result}") return result
Made that look *way* too easy. I spent a whole hour last night trying to get the first line of code to work! It was because my Python paths were thrown about the place
How to build the js part of code to generate umd.js file in dist folder. I am build using yarn build but the generated umd file is not working and not opening new panel. Please help
How to build the js part of code to generate umd.js file in dist folder. I am build using yarn build but the generated umd file is not working and not opening new panel. Please help
Great question. Try `yarn install` as well. Make sure that the plugin is in your plugins directory. And when you want to change the plugin, make sure you use `yarn dev`. If you have more questions about FiftyOne Plugins, check out the #plugins channel in the FiftyOne community Slack! slack.voxel51.com/
This is good! But i believe the data should also grab eye movement. Eye movement is crucial to map intention and will aid in robot navigation. Apple's headset has the hardware to monitor both eye direction and head direction.
Is it possible to use this and find the most similar image given user submitted photos? For example I'm trying to do something to detect trading cards, where the input would be photos of cards submitted by users.
There is lots of documentation online on their website, check it out! Its really not difficult to get it running, but its "only" an API, so some python Experience is definetly helpful to get it running. :)
There is lots of documentation online on their website, check it out! Its really not difficult to get it running, but its "only" an API, so some python Experience is definetly helpful to get it running. :)
"Wow, this video is incredibly informative and well-produced! The speaker does a fantastic job of explaining the complex topic of speech recognition and the new Whisper model from OpenAI in a way that's easy to understand. Great job, highly recommended to anyone interested in this field!"
As mentioned in the video, fiftyone isn't a classical annotation tool, but it provides hooks to do that with cvat, labelbox etc and then load the labeled data back into fiftyone. For me the cvat solution worked perfectly fine. Everything is perfectly documented on their website, check it out! :) If you want to load your annotation data which is in your own format, and not in a typical dataformat (COCO,...) you'll have to write a few lines of python codes yourself. For that purpose I have implemented a DatasetHandler-class. You'll have to convert into fiftyone-format by iterating through your data and turn them into fiftyone Detection-Objects: detections.append( fo.Detection(label=my_label, bounding_box=my_bbox) ) Fiftyone doesn't work "out of the box", but it's a great tool for working with CV-Data!
Hi I am getting the following error in colab and jupyter notebook with custom data and coco 2017 (default data) MalformedQueryException: Cannot attach/detach dataset to/from a batch project Kindly help me to solve this issue
I had trouble with it so created a conda virtual env on 3.6 and moved my java installation to path. Now the app is loading fine and also the open images dataset is downloading fine. There is so much capacity with this library. As a beginner in those while endeavor my mind is blown.
