Home/ Machine Learning Software/ V7 Darwin/ Reviews
Receive access to its neural network training and automated picture annotation
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Very user friendly platform wich alows for easy annotation and moving on with projects
Not much things to dislike so far, would love to be able to use lines in the consensus stage.
Heloping with automation and measurement of otic nerve diameter
ability to automate repetitive tasks and improve efficiency in the annotation process. It can also provide tools for quality control, such as duplicate detection and annotation consistency checks
the tool is not user-friendly or intuitive, making it difficult for users to navigate and utilize all of its features and thus i think the interface and help feature must be improved
it helps solve problems related to data annotation and labelling, which can be a time-consuming and tedious task by automating and streamlining this process. Its reporting feature helps to know the progress of the team
With V7 time-consuming tasks such as notes are performed in a very agile way. In addition, you can create and manage your scientific workflows with a very intuitive interface.
I'm still starting to use it, so far no problems.
The incredible ease and speed of the annotation generation process
After several tries trying out various tools to annotate my data, I stumbled on V7 and immediately realised that V7 had exactly what I needed. My datasets have a lot of similar images and V7's copy annotations feature helps save a ton of time and allows me to work through my datasets swiftly. Furthermore, I never knew I needed the image manipulation options that V7 provides until I used it. It allowed me to completely isolate my items from the noise for more accurate annotations.
Also, V7's UI looks amazing and is incredibly simple to use. There's no learning curve.
No complaints so far, as I haven't encountered any features that I dislike. Everything is straightforward to use, and I haven't encountered any bugs while using V7 either.
V7 is a data annotation tool with features such as "Copy Annotations" that allows for a faster workflow. I'm currently annotating my images with bounding boxes, but V7 also provides various other options.
I am using v7 labs AI tool for my research on Computer Vision. Especially for annotating data and training CV models. I must say that V7 is the most innovative and amazing tool in this category. I am fascinated by this platform's features, from annotating datasets to training and deploying. It's really wonderful to have all these managed wonderful features. The data annotation tool on the platform is extremely powerful, well-featured, and easy to use. I can now label my dataset in a few clicks, even the most complex objects with amazing auto-annotation features, even for polygon shapes. I also tried 3d annotation of objects in the image using a cuboid tool that it provides, and it's fantastic. I really recommend v7 labs to everyone who is Computer Vision Pro and wants to annotate and build efficient and accurate computer vision models and manage the whole pipeline/workflow. Thank you, v7 labs team for such a great platform.
There is nothing that I dislike so far. All features are really amazing.
I can annotate image and vedio dataset quickly and I can build accurate Computer Vision Models .
Personally, I have learned a lot using V7 Darwin and we have benefitted as a company from its Annotation Tools and Interface. The UI is straightforward and the tools are clearly laid out, making the platform less difficult to understand compared to others. With just a few hours of exploration, a beginner can get used to the tools and shortcuts. At least that's how it was for me. We were tasked with labeling a very demanding project a while ago and it was thanks to Darwin's precise Polygon tool, merge/separation tools and visible time tracking on the interface, that we were able to deliver accurate-high quality labels in good time. Darwin is definitely my first choice if 'Speed and Accuracy' are the main targets.
Nothing bad if I'm being honest. If you could pitch in an image searching pane for users so we choose the asset we want to work on? V7 is my go-to!
Safety netting. With the ease of V7 as a user, I am more confident in how I annotate because my dots connect and my labels come out as they should. And fast!
I love their UI. Very user friendly. Easy panning of images that helps speed up annotation. Their shortcuts aren't limited, everything you want to do has a key for it, which makes annotation easy. Most especially, I love their label count feature and the image manipulation feature! Amazing stuff. I can confidently say it is the best UI for data annotation I have ever come across.
This feature is definitely the team's favorite and something that sets V7 apart from other labeling platforms. Annotation time reduced significantly and enabled us create multiple instances of the various tools or classes by just hitting "N"
We really like the open API. We could easily export our data and create over a thousand classes via the CLI SDK. Quite impressed with it. Made my life easy for one.
Importing and exporting data in multiple formats, including Geotiff, was a nice surprise and proved quite helpful.
Occasional platform lags and sign-outs is an annoyance but everything else on the platform is great. Also, the inabilty to get worker stats on a project in a more explicable format, even without exporting.
I'd recommend implementing Lidar Annotation Tools, though. It'd be a plus for you and your customers.
I really like the QA process workflow as it allows us review annotations easier and in stages. v7 handles magnitude data which give its users an understabable view of what data one is to work on. From Admin control to Workforce Manager control Worker control, everything makes sense. The self-assigning feature is a plus for data pools
My company performs a lot of data labelling using multiple platforms - we choose V7 frequently for Computer Vision projects due to the ease of managing workflows and quality control stage gates, the simplicity of the UX, the auto-annotate feature - and the fact that its preferred by our annotators. They also have a fantastic and highly responsive team.
Not much honestly. Not as strong on NLP yet (or certain data types like LIDAR) but I expect this might be a growth area for the company, and I wouldn't be surprised if they tackle these areas with the same zeal and competency should they choose to invest in them.
We use V7 to produce high-quality data annotation pipelines with large data sets and large teams - the platform facilitates this activity in a way that most alternatives don't come close to, in everything from the open API, UX, data security assurance, handling large volumes etc...
- powerful API and tooling to quickly generate interpolated annotations which is so valuable for our unstructured data use case
- quick and responsive support
- active product roadmap with more great features coming
we've made some additional product requests around immutable video metadata and workflow management which are actively being worked on
Generating tons of annotations for cheap. This is so valuable for us as my team is working with a particularly messy and large microscopic dataset of cell imagery
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"V7 Darwin is accurate, user-friendly and functional, a wide variety of tools make annotation relatively quick and easy.
The subtract and merge options are particularly useful for pixel-perfect labeling which is a big plus and not something I've seen elsewhere, the experience so far has been smooth with no issues. V7 is my go-to platform."
"Not much to say here, the platform works well with no hindrance, and the work is promptly saved and easily retrieved. No problems. The platform does not freeze and makes for a smooth experience."
"V7 gives the annotator a wide variety of tools to handle any form of computer vision project. The platform also provides auto annotations which save time and make for a pleasant work experience."