SuperAnnotate Pro
SuperAnnotateReviews from AWS customer
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Easy to use and to set up- All needed functions are there.
What do you like best about the product?
Setup, player functionalities. Sensitive data stay on our servers
What do you dislike about the product?
It is quite expensive on full price after test period.
What problems is the product solving and how is that benefiting you?
Annotation, data analyses
Highly effective and fast for image annotations
What do you like best about the product?
SuperAnnotate's editor has a vast variety of functionalities, which makes the annotation process smooth and fast.
What do you dislike about the product?
Not much, however, I would improve the UI a little.
What problems is the product solving and how is that benefiting you?
Since we are a wine-producing company, the main goal was to annotate our grape fields, to classify them by types. SuperAnnotate's tooling allowed us to streamline the annotation process for more effective results.
Effective collaborative platform
What do you like best about the product?
The online collaborative features - enabling a diverse team to tag as well as perform QA/QC in a verifiable workflow. This includes variable work schedules, locations, etc.
What do you dislike about the product?
Nothing to date. The only hiccup we had initially was compiling of the tags via various datasets. We used their github script, which we initially struggled with, however, the support was quick and responsive to getting it solved on our end. a
What problems is the product solving and how is that benefiting you?
Annotating natural features, where the contrast and colors are extremely similar. The unique platform enables team members to work on various computers and in various time zones.
SuperAnnotate is user friendly and helps you to annotate very fast
What do you like best about the product?
It is very useful for the vector data, especially nowadays everyone is looking for correct annotation software and this superAnnotate is highly recommendable to the teams who want their raw data to be annotated very precisely and quickly.
What do you dislike about the product?
Previously after one release I faced an issue regarding the status of image. I was unable to move image from one state to other state (QA state) and I have contacted the customer support and with in a short span of time it was resolved. Now every thing looks okay for me.
What problems is the product solving and how is that benefiting you?
We can annotate our raw images super fastly by using this software and it helped us to complete the project on time. We are able to complete 100 k annotations in a short period and helped our AI team to build a model. The results are pretty good and our AI team deployed the model into web APP.
Recommendations to others considering the product:
SuperAnnotate is useful for the users who wanted their data to annotate with more precision and also there are several methods to upload your images in to superAnnotate like from s3 bucket, through sdk, from local machine etc.
Efficient Platform, Great Support Team
What do you like best about the product?
User-friendly and efficient labelling platform supporting data annotation for various ML tasks. Professional and accessible support team.
What do you dislike about the product?
Nothing specific that I can mention. Very good experience so far.
What problems is the product solving and how is that benefiting you?
Providing an efficient and accessible platform for dataset annotation. This conveniently provides the training data needed to develop various machine learning models.
Precise and concise
What do you like best about the product?
Very user friendly, visually pleasing as well
What do you dislike about the product?
Could be hard to comprehend for beginners
What problems is the product solving and how is that benefiting you?
Giving us key insight into training and helping our users benefit through easy and comprehensive ways to learn
All-in-one platform and services
What do you like best about the product?
SuperAnnotate has well-built automation features that makes the annotation process less time-consuming. Smart segmentation is a good example.
What do you dislike about the product?
Nothing significant that SuperAnnotate did not address in time.
What problems is the product solving and how is that benefiting you?
We were working on various annotation projects and the team used SuperAnnotate to label our data. The annotation tool was easy to work with regardless of project complexity.
Super Annotate is very user friendly tool for any and every kind of annotation we can think of.
What do you like best about the product?
User-friendly tool,
QA interface
End to end platform for annotations
QA interface
End to end platform for annotations
What do you dislike about the product?
Absolutely nothing, it is one of the best tools we have used so far.
What problems is the product solving and how is that benefiting you?
We use SuperAnnotate for data labeling using vector, pixel and BB. We have been able to achieve accurate results and a high-quality dataset of annotations.
SuperAnnotate makes image annotation for large datasets effortless
What do you like best about the product?
The ease of use of the platform within a project team for image annotation and project management is unparalleled.
What do you dislike about the product?
Nothing in particular for the task I use it for, but more can be done on the aspect of compatibility with different annotation styles
What problems is the product solving and how is that benefiting you?
I generally use SuperAnnotate for image annotations to be used in computer vision projects. It has made the collaborative image annotation process smooth, and speed up the time spent in the process
Great Platform, Fast Project Delivery!
What do you like best about the product?
The editor is easy to use and is being constantly improved.
What do you dislike about the product?
There isn’t anything I didn’t like. Plus SuperAnnotate’s support team is quick to respond.
What problems is the product solving and how is that benefiting you?
We needed our model to identify flaws in the documentation. Our first batch was completed quicker than we anticipated due to the proficiency of the team handling our project.
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