Labelbox Reviews
(Rated by 15 users)
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Payment Methods
- Credit/Debit Cards
Payment Methods
- Verified Store VERIFIED
- Free shipping: Orders $50+
- In-store pickup: Ready in 2 hours
- 30-Day Returns
- Gap Good Rewards (4 brands)
Payment Methods
- Tops: $23 - $70
- Bottoms: $27 - $70
- Outerwear: $34 - $70
- Kids: $29 - $75
Overall Rating
4.0
Base on 15 Reviews
Ratings by Feature
Ratings by Feature
- Price & Quality4.7
- Customer Service4.5
- Good Value4.8
Recent Customer Reviews (15)
Vitoria Silva
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René Schuhmacher
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William Delk
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Lindsay Storm
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Harry Bartlett
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Virginia Page
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Kristin Dahms
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George Walker
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Logan Morris
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Chappell Devost
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Payment Methods
Accepted Payment Options:
Prices for items on Labelbox.com vary widely depending on the type of clothing and promotions available. Typical price ranges include:
Credit/Debit Cards
Payment Process
- Payments can be made online during the checkout process.
- For Labelbox credit card payments, options include online payments, mail, or phone calls, but in-store payments are not accepted.
Refund Information
Refunds for returns will be processed back to the original payment method used during the purchase.
Labelbox Pros & Cons
Pros
1
Model assisted labelling: This feature is so accurate that data preparation time is reduced to a big extent.
2
Ease of use: Users have praised its user-friendly interface.
3
Data Management: It provides inbuilt searching, sorting, saving a subset of the datasets options which really make data handling much easier.
CONS
1
Complex Interface: Despite its positive reviews, some users have expressed difficulty in navigating through Labelbox’s interface.
2
Lackluster Support: A common grievance is the delay in receiving technical support from Labelbox.
3
Buggy Performance: It can be buggy if we need to process images with higher resolution.
Labelbox Features and Benefits
Features
Data Labeling
Custom labeling and review workflows are available to create high-quality training data.
Data Curation
It provides AI-ready datasets.
Model Evaluation
Compare predictions and ground truth.
Reinforcement Learning with Human Feedback (RLHF)
This feature allows for the integration of human feedback into the reinforcement learning process.
Data Engine
Curate, annotate, and evaluate data.
Model Assisted Labeling
Pre-label data with foundation models. This feature is so accurate that data preparation time is reduced to a big extent.
Reports
Analytics and performance dashboard.
Human Expert Evaluation
Evaluate models with human experts.
Foundry
Enrich data using foundation models.
Boost Expert Workforce Services
Scale up capacity with Boost Workforce labeling services.
Multimodal Data Labeling
Supports multimodal data labeling, AI-assisted data generation, and human-centric benchmarking.
Ease of use
Users have praised its user-friendly interface.
Data Management
It provides inbuilt searching, sorting, saving a subset of the datasets options which really make data handling much easier.