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officially out of beta #263

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merged 3 commits into from
Oct 9, 2024
Merged

officially out of beta #263

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b2b6367
officially out of beta
brandon-groundlight Oct 9, 2024
f7bd9c1
Do some other cleanup while I'm at it
brandon-groundlight Oct 9, 2024
50e4c51
correct path
brandon-groundlight Oct 9, 2024
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2 changes: 0 additions & 2 deletions README.md
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Expand Up @@ -24,8 +24,6 @@ print(f"The answer is {image_query.result}")

Your images are first analyzed by machine learning (ML) models which are automatically trained on your data. If those models have high enough confidence, that's your answer. But if the models are unsure, then the images are progressively escalated to more resource-intensive analysis methods up to real-time human review. So what you get is a computer vision system that starts working right away without even needing to first gather and label a dataset. At first it will operate with high latency, because people need to review the image queries. But over time, the ML systems will learn and improve so queries come back faster with higher confidence.

_Note: The SDK is currently in "beta" phase. Interfaces are subject to change in future versions. We will follow [semver](https://semver.org/) semantics for breaking changes._

## Learn more

Some more resources you might like:
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2 changes: 0 additions & 2 deletions docs/docs/getting-started/getting-started.mdx
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Expand Up @@ -14,8 +14,6 @@ image_query = gl.submit_image_query(detector=det, image=img)
print(f"The answer is {image_query.result}")
```

_Note: The SDK is currently in "beta" phase. Interfaces are subject to change in future versions. We will follow [semver](https://semver.org/) semantics for breaking changes._

### How does it work?

Your images are first analyzed by machine learning (ML) models which are automatically trained on your data. If those models have high enough [confidence](docs/building-applications/4-managing-confidence.md), that's your answer. But if the models are unsure, then the images are progressively escalated to more resource-intensive analysis methods up to real-time human review. So what you get is a computer vision system that starts working right away without even needing to first gather and label a dataset. At first it will operate with high latency, because people need to review the image queries. But over time, the ML systems will learn and improve so queries come back faster with higher confidence.
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2 changes: 1 addition & 1 deletion pyproject.toml
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Expand Up @@ -9,7 +9,7 @@ packages = [
{include = "**/*.py", from = "src"},
]
readme = "README.md"
version = "0.18.1"
version = "0.18.2"

[tool.poetry.dependencies]
# For certifi, use ">=" instead of "^" since it upgrades its "major version" every year, not really following semver
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