search

pucardotorg / dristi_experiments

For Pucar Solutions Team
2 stars 4 forks source link

motion blur model & inference script #26

Closed kartikbhtt7 closed 3 months ago

kartikbhtt7 commented 3 months ago

Summary by CodeRabbit

coderabbitai[bot] commented 3 months ago

Walkthrough

The recent changes introduce a blur detection feature for images of documents. This includes a new Docker environment setup, an API for blur classification using Hypercorn, image processing utilities, and enhanced functionality for handling requests and models. The feature leverages an SVM model for classification and provides comprehensive documentation and error-handling within the system.

Changes

Files Summary
blur_detection/Dockerfile Sets up a Python 3.9-slim Docker environment, installs dependencies, copies code, exposes port 8000, and runs the server using Hypercorn.
blur_detection/README.md Details instructions for building and running the blur detection model using Docker, with example API calls and JSON response formats.
blur_detection/__init__.py Imports entities from request.py and model.py.
blur_detection/api.py Defines a web service to classify images as blurry or not using a machine learning model; includes routes and initialization routines.
blur_detection/model.py Implements the Model class that loads an SVM model from Hugging Face and classifies images based on edge features. Adds create and classify_image methods.
blur_detection/request.py Introduces ModelRequest to handle model requests with a method to convert objects to JSON. Adds to_json method.
blur_detection/requirements.txt Specifies updated project dependencies for various Python packages needed.
blur_detection/utilities.py Adds functions for image normalization, edge feature computation, and statistical feature calculation.
run/blur_script.py Introduces functionality to classify images using a local server, save results as JSON files, and handle errors asynchronously. Adds multiple utility functions and a main execution block.

Sequence Diagram(s)

sequenceDiagram
    participant Client
    participant API
    participant Model
    participant Utilities

    Client->>+API: POST /classify-image (Image File)
    API->>+Model: Initialize Model
    Model->>Utilities: Process Image
    Utilities->>Model: Return Features
    Model->>API: Classification Result
    API->>-Client: JSON Response

Poem

Here comes a rabbit, coding with delight,
Enhancing blur detection, day and night.
With Docker's might and Hypercorn's speed,
This model caters to every need.
JSON responses, clear and bright,
Classify those images, wrong or right! 🚀

[!TIP]

AI model upgrade ## `gpt-4o` model for reviews and chat is now live OpenAI claims that this model is better at understanding and generating code than the previous models. Please join our [Discord Community](https://discord.com/invite/GsXnASn26c) to provide any feedback or to report any issues.

Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media?

Share - [X](https://twitter.com/intent/tweet?text=I%20just%20used%20%40coderabbitai%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20the%20proprietary%20code.%20Check%20it%20out%3A&url=https%3A//coderabbit.ai) - [Mastodon](https://mastodon.social/share?text=I%20just%20used%20%40coderabbitai%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20the%20proprietary%20code.%20Check%20it%20out%3A%20https%3A%2F%2Fcoderabbit.ai) - [Reddit](https://www.reddit.com/submit?title=Great%20tool%20for%20code%20review%20-%20CodeRabbit&text=I%20just%20used%20CodeRabbit%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20proprietary%20code.%20Check%20it%20out%3A%20https%3A//coderabbit.ai) - [LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fcoderabbit.ai&mini=true&title=Great%20tool%20for%20code%20review%20-%20CodeRabbit&summary=I%20just%20used%20CodeRabbit%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20proprietary%20code)
Tips ### Chat There are 3 ways to chat with [CodeRabbit](https://coderabbit.ai): - Review comments: Directly reply to a review comment made by CodeRabbit. Example: - `I pushed a fix in commit .` - `Generate unit testing code for this file.` - `Open a follow-up GitHub issue for this discussion.` - Files and specific lines of code (under the "Files changed" tab): Tag `@coderabbitai` in a new review comment at the desired location with your query. Examples: - `@coderabbitai generate unit testing code for this file.` - `@coderabbitai modularize this function.` - PR comments: Tag `@coderabbitai` in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples: - `@coderabbitai generate interesting stats about this repository and render them as a table.` - `@coderabbitai show all the console.log statements in this repository.` - `@coderabbitai read src/utils.ts and generate unit testing code.` - `@coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.` - `@coderabbitai help me debug CodeRabbit configuration file.` Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments. ### CodeRabbit Commands (invoked as PR comments) - `@coderabbitai pause` to pause the reviews on a PR. - `@coderabbitai resume` to resume the paused reviews. - `@coderabbitai review` to trigger an incremental review. This is useful when automatic reviews are disabled for the repository. - `@coderabbitai full review` to do a full review from scratch and review all the files again. - `@coderabbitai summary` to regenerate the summary of the PR. - `@coderabbitai resolve` resolve all the CodeRabbit review comments. - `@coderabbitai configuration` to show the current CodeRabbit configuration for the repository. - `@coderabbitai help` to get help. Additionally, you can add `@coderabbitai ignore` anywhere in the PR description to prevent this PR from being reviewed. ### CodeRabbit Configration File (`.coderabbit.yaml`) - You can programmatically configure CodeRabbit by adding a `.coderabbit.yaml` file to the root of your repository. - Please see the [configuration documentation](https://docs.coderabbit.ai/guides/configure-coderabbit) for more information. - If your editor has YAML language server enabled, you can add the path at the top of this file to enable auto-completion and validation: `# yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json` ### Documentation and Community - Visit our [Documentation](https://coderabbit.ai/docs) for detailed information on how to use CodeRabbit. - Join our [Discord Community](https://discord.com/invite/GsXnASn26c) to get help, request features, and share feedback. - Follow us on [X/Twitter](https://twitter.com/coderabbitai) for updates and announcements.