In machine learning, pixel segmentation goes beyond the treasure chest of bbox detection. Instead of just marking the general location of objects, it delves deeper to create a detailed map of each object, pixel by pixel. Imagine a treasure map where each piece of gold, diamond, or jewel is meticulously outlined. That’s the power of pixel segmentation. The model is trained on a treasure map dataset, where each image has a corresponding “segmentation map” highlighting every object’s individual pixels. Deep learning models like U-Net, Mask RCNN and DeepLab are adept at this fine-grained analysis. After training, the model can meticulously segment objects in unseen images, revealing intricate details. This skill is invaluable in tasks like self-driving cars where understanding the shape and size of objects precisely is crucial, or medical imaging where segmenting specific tissues or organs is essential for diagnosis.
Unleash the power of pixel-perfect image analysis with our industry-leading pixel segmentation services. We supercharge your computer vision models with meticulously labeled segmentation masks, enabling superior object recognition and fine-grained detail extraction. Our team of experts meticulously hand-labels each pixel, ensuring precise class allocation for every image element. Rigorous quality control guarantees that every mask adheres to the strictest accuracy standards. Furthermore, our streamlined workflows deliver exceptional results at competitive rates, making us the ideal partner for all your segmentation needs. Whether you’re a pioneering startup or a global enterprise, we tailor our solutions to your specific project requirements. By partnering with us, you gain more than just an annotation service; you gain a trusted advisor to unlock the full potential of pixel segmentation and achieve groundbreaking results.
- We accommodate both image and video formats for pixel segmentation. In images, we aim to classify each individual pixel within the frame, assigning it a specific class label based on the content it represents. For videos, pixel-wise classification is applied to every frame, effectively segmenting and labeling objects throughout the video.
- Streamlining the process, we eliminate the need for a specific folder structure on your end. Our internal systems efficiently manage all organizational aspects.
Samples
Transparent Pricing Structure
We follow a clear pricing structure for our pixel segmentation annotation services. Here’s a breakdown of the key pricing structure:
- Fixed Fee for Small Batches: Up to 10,000 annotations cost a flat fee of $100 per batch, regardless of the number of images within that batch.
- Per-Annotation Pricing for Larger Batches: For batches beyond 10000 annotations, you pay $0.01 per annotation.
To initiate work, you prepay a portion of the total cost based on the batch size, tiered upfront payments are as follow:
- $100 for batches between 10,000 and 50,000 annotations.
- $500 for batches between 50,000 and 200,000 annotations.
- $2,000 for batches between 200,000 and 400,000 annotations.
- 25% upfront payment for batches exceeding 400,000 annotations.
After the annotations are complete, you pay the remaining balance based on the per-annotation cost.
Understanding Project Complexity
We understand that for some projects, especially those involving complex or subjective pixel segmentation tasks, accurately estimating the number of annotations upfront can be challenging. We offer flexibility in such cases:.
- Estimated Annotation Range: If you're unsure of the exact number of annotations needed, you can provide an estimated range. We'll quote based on that range with a buffer to account for potential variations.
- Pilot Batch Option: For highly complex projects, consider a pilot batch of a few thousand images. This allows us to assess the annotation difficulty and provide a more accurate quote for the entire project.
- Flexible Payment Adjustments: During the annotation process, if the actual number of annotations deviates significantly from the initial estimate, we can adjust the final cost accordingly.
Transparency and Communication
To ensure a smooth and collaborative process we aim for clear communication, centralized information management, and the flexibility to adapt to the specific needs of your project:
- Ticketing System: We recommend creating a ticket in our system to centralize all communication regarding your project. Through the ticket system, we can easily track progress reports, answer your specific questions and requirements, and discuss any adjustments needed throughout the annotation process.
- Open Communication: We believe in open communication. We'll keep you informed about the annotation progress through the ticketing system and proactively reach out if any potential adjustments to the initial estimate are necessary due to project complexity.