Labelgpt
3.21
0
LabelGPT automatically annotates images using AI, supports multiple sources, and integrates with cloud and ML operations.
Labelgpt Reviews
3.21
Based on 14 reviews
Arjun Nair
January 16, 2025
What do you like most about using Labelgpt?
I love the integration with cloud platforms like GCP, which makes my data management much easier.
What do you dislike most about using Labelgpt?
The initial learning curve can be steep for new users, which might discourage some from fully utilizing the tool.
What problems does Labelgpt help you solve, and how does this benefit you?
It solves the problem of manual annotation, which is both time-consuming and costly. The efficiency gained allows my team to focus on analysis rather than data input.
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Asha Okeke
January 13, 2025
What do you like most about using Labelgpt?
I appreciate the quick setup and cloud integration features. It allows me to easily work with images stored in AWS.
What do you dislike most about using Labelgpt?
The confidence score filtering feature is not very reliable, leading to some inconsistent results.
What problems does Labelgpt help you solve, and how does this benefit you?
It helps streamline the annotation process for machine learning models, saving time. However, it still requires manual intervention, which can be frustrating.
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Yuki Tanaka
January 8, 2025
What do you like most about using Labelgpt?
The AI's ability to generate labels based on text prompts is fascinating and often accurate.
What do you dislike most about using Labelgpt?
The processing speed can be slow at times, especially with large datasets.
What problems does Labelgpt help you solve, and how does this benefit you?
It helps in accelerating the image annotation process, which is crucial for my research projects, but I often need to double-check the results.
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Sophie Rinaldi
January 6, 2025
What do you like most about using Labelgpt?
The tool is relatively easy to set up, and I like the AI's potential to improve over time.
What do you dislike most about using Labelgpt?
The tool sometimes struggles with complex images, leading to less accurate annotations.
What problems does Labelgpt help you solve, and how does this benefit you?
It helps speed up the labeling process, but the quality of the output can be inconsistent, which adds to the workload.
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Nia Mthembu
January 1, 2025
What do you like most about using Labelgpt?
The smart quality assurance feature gives me confidence in the labeling process, ensuring a higher standard.
What do you dislike most about using Labelgpt?
The lack of support for certain image formats can be limiting for my projects.
What problems does Labelgpt help you solve, and how does this benefit you?
It streamlines the workflow in my machine learning projects, saving time and effort that I can allocate to other areas of development.
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Emily Bennett
December 24, 2024
What do you like most about using Labelgpt?
The analytics tools are useful for project management and tracking progress.
What do you dislike most about using Labelgpt?
The lack of customization options can be a drawback as I prefer more flexibility in my tools.
What problems does Labelgpt help you solve, and how does this benefit you?
It reduces the time needed for manual annotation significantly, but the limited customization means I can’t tailor it to my specific workflow needs.
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Thomas Klein
December 19, 2024
What do you like most about using Labelgpt?
The integration with machine learning operations is seamless, making it easy to export directly into my ML models.
What do you dislike most about using Labelgpt?
The customer support response time could be improved; I experienced delays in getting my questions answered.
What problems does Labelgpt help you solve, and how does this benefit you?
It helps automate the labor-intensive process of labeling images, which is crucial for training accurate models, although I sometimes need to verify the output.
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Darya Sokolov
December 14, 2024
What do you like most about using Labelgpt?
The idea of automatic annotation is fantastic and could greatly improve productivity.
What do you dislike most about using Labelgpt?
Unfortunately, the execution is lacking. I've had too many issues with incorrect labels and segmentation errors.
What problems does Labelgpt help you solve, and how does this benefit you?
It has the potential to help with the tedious task of labeling images, but the inaccuracies mean I still have to spend a lot of time fixing errors.
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Khalid Al-Mansoori
December 11, 2024
What do you like most about using Labelgpt?
The automated label generation concept is impressive and saves time.
What do you dislike most about using Labelgpt?
In practice, it often fails to deliver accurate labels, leading to frustration.
What problems does Labelgpt help you solve, and how does this benefit you?
While it aims to streamline the annotation process, the inaccuracies mean I still need to spend significant time correcting errors, negating its initial time-saving promise.
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Li Chen
December 5, 2024
What do you like most about using Labelgpt?
The generative AI model does a great job in segmenting and labeling images accurately, which has improved my workflow.
What do you dislike most about using Labelgpt?
Sometimes the software can be slow, especially when processing high-resolution images.
What problems does Labelgpt help you solve, and how does this benefit you?
It significantly reduces the time spent on image annotation, allowing for quicker project completion. However, it does require careful review to ensure label quality.
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Liam O'Sullivan
December 1, 2024
What do you like most about using Labelgpt?
The ease of integrating with various cloud services is a major plus for me.
What do you dislike most about using Labelgpt?
The labeling inaccuracies can sometimes hinder the overall productivity of the team.
What problems does Labelgpt help you solve, and how does this benefit you?
It automates many of the tedious aspects of image labeling, which allows my team to focus on more complex tasks.
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Clara Koster
November 29, 2024
What do you like most about using Labelgpt?
The AI-driven automation is impressive, and it does save a lot of time on repetitive tasks.
What do you dislike most about using Labelgpt?
I've encountered some bugs that can disrupt the workflow, which is frustrating.
What problems does Labelgpt help you solve, and how does this benefit you?
It helps automate the labeling process for machine learning training datasets, which is beneficial, but the inconsistencies in output quality can be a setback.
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Mohamed Said
November 22, 2024
What do you like most about using Labelgpt?
The ability to automate image annotation is quite impressive. It saves me a lot of time when working on projects that require large datasets.
What do you dislike most about using Labelgpt?
The interface feels outdated and not very user-friendly. Sometimes, I find it hard to navigate through the options.
What problems does Labelgpt help you solve, and how does this benefit you?
Labelgpt helps reduce the workload for image labeling, which is especially beneficial when dealing with extensive image databases. However, I wish the output accuracy was higher, as I still have to verify many of the labels.
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James Mason
November 19, 2024
What do you like most about using Labelgpt?
The automated labeling feature is a real game-changer, especially for large datasets.
What do you dislike most about using Labelgpt?
The pricing seems a bit steep for small teams, especially when compared to alternatives that offer more user-friendly interfaces.
What problems does Labelgpt help you solve, and how does this benefit you?
It helps in speeding up the annotation process, allowing me to focus on other tasks. However, I often find myself having to redo labels, which offsets some of that time savings.
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