aipanthers

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Utilize Computer Vision to Enhance Government Operations security procedures for rigs and pipelines.

Boost Security for Everyone

Simplify corporate processes by deploying computer vision to manage safety procedures and pipeline inspections.

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Quickly Recognize Component Failures

Utilize current photo and video data to let machine vision quickly identify deteriorated pipeline components and changes in the surroundings. Get early warnings to avoid serious issues with productivity and the environment.

Secure Your Workforce

Through constant monitoring of adherence to safety protocols, such as identifying the wearing of personal protective equipment (PPE) during the workday, trained computer vision models can contribute to the maintenance of safety standards."

Instead of weeks, create a trained model in a matter of hours.

Integrating AiPanthers with top labeling services and training tools is simple.

After installation, keep your model updated and growing.

You can deploy and scale your models as your data increases with AiPanthers, which serves as a central point for handling your datasets. Identify and classify errors with ease, modify configurations, and investigate other labeling and training options.

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Improve Model Performance with Less Data Needed

With AiPanthers, you can create computer vision models that are more accurate while utilizing fewer photos.

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Tiling

Split up your high-resolution photos into manageable chunks. In order to accurately categorize faults by kind and severity, this preprocessing phase makes it easier to recognize minute objects, patterns, or fine features.

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Version Control

Versions of the dataset allow for rapid testing of various labeling and training techniques. Make changes, create exports, and continue without a hitch.

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Augmentations

By generating skewed or warped versions of your original photos, you can generate more training data without using new images. This simulates various viewpoints and angles, which helps increase model correctness.

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Advanced Health Check

Practical visualizations, such as class distribution breakdowns, dimension analysis, and an annotation heatmap, that provide insights into the quality of your dataset and make recommendations for changes

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