Deep Block supports the following image file formats: png, j2k, jpg, geotiff, tiff, bmp, and jp2.

Deep Block supports high-resolution files up to 40GB per EACH. There is no limit to the number of images you can upload to Deep Block.
Contact Us if you need to want to upload a larger image file.

The number of annotations needed to train an AI model depends on various factors, such as:

• the complexity of the problem
• the type and quality of data
• the algorithms used 

In general, the more annotations you have, the better the performance of the AI model will be.

For instance, image classification models might require at least thousands of labeled images to achieve high accuracy. Object detection models might need hundreds to thousands of labeled images, depending on the complexity and variability of the objects to be detected. Image segmentation models typically require pixel-level annotations for a smaller set of images. (at least a few hundred for each class)

In any case, it is important to ensure that the annotations are accurate, consistent, and representative of the real-world data to avoid bias and improve the robustness of the AI model. The number of annotations needed to achieve this will depend on the specific use case and the quality standards required.

As a good practice, it is better to test-train your model progressively and validate its performances. If you have any doubt, feel free to contact us directly.

Deep Block enables its users to share projects among themselves.

• Shared projects: Users can share their projects privately with other users directly and invite them to collaborate.
• Project Store: Users can upload their projects to the Project Store for others to use.
• Public projects: Users can make their project public so that other users may offer their help to complete it.

Therefore, the main difference between shared projects and public projects is the willingness to either work in a small private circle or in a more open environment with other Deep Block users.

You can export your inference output of Deep Block directly in a COCO JSON format. You can also use the Deep Block API to integrate directly with your applications. Contact us if you want a trained model with weights in a file format.

You can choose a plan depending on your computational needs. Or contact us for enterprise license. 

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