Row 7456

Row ID: 7456 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 7456 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

At my line of work, I have to take a picture, detect/segment tens up to hundreds of points of interest and summarize it's sizes.

I have ML model that is mostly precise but makes few stupid mistakes so it's not perfectly reliable (as expected) and occasionaly needs manual intervention that corrects it's output.

Currently, I use

1) CVAT to upload an image, run prediction and correct/approve the results. Then I download the image and apply

2) Python script to run postprocessing

This workflow is good for few projects and few relatively-savy users but as time passes projects pile up and team grows. At the moment, there are several different tasks, each needs a bit different posprocessing and more and more people working with it.

**Do you know any software that can help me to implement this workflow without manually showeling data from CVAT to scripts?**

I looked around if it's possible to extend CVAT but it's meant as annotation tool not a link in a production chain so I didn't found anything (appart plugging my own models into it). As an alternative I was thinking about writing my own solution. I would be able to write a backend but I cannot write the frontend part. I don't know javascript and searching through github for any decent frontend supporting tools (like brushes for segmentation) and label handling(fix mislabeled stuff etc) led nowhere so I gave up thinking about it.

FieldValue
text At my line of work, I have to take a picture, detect/segment tens up to hundreds of points of interest and summarize it's sizes. I have ML model that is mostly precise but makes few stupid mistakes so it's not perfectly reliable (as expected) and occasionaly needs manual intervention that corrects it's output. Currently, I use 1) CVAT to upload an image, run prediction and correct/approve the results. Then I download the image and apply 2) Python script to run postprocessing This workflow…
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-05-16
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url_encoded Z0FBQUFBQm5Lak9ISmxqQ0V6eGpwZzhSU0FfTGZJY1ZXYUdYZEgzYkdJaHBZS29nUTNTT3A1dUU1TjM4RnQtaTRHSU5paW4xMUx6cW02NjVHVlNNRzRYWHhYLUVVajdnNEtUbm94ZXdUdVo3aWhOcWxtQkZnT3BxOG5xTy1ZUmpwUVBFd0ZIbzhNWTYyTy1DUlJiVHNHN0VWUDJxRlBnajlZOWU4Y3NtS0VUVzdMQjF4bHFkUUVhb2s3c0U3X1pIUUl3aHI5ZElIUFliQjFrTlhlZ1AtejA2WVNqQUlwSTRnUT09

Raw Record

{
  "text": "At my line of work, I have to take a picture, detect/segment tens up to hundreds of points of interest and summarize it's sizes. \n\nI have ML model that is mostly precise but makes few stupid mistakes so it's not perfectly reliable (as expected) and occasionaly needs manual intervention that corrects it's output.\n\nCurrently, I use \n\n1) CVAT to upload an image, run prediction and correct/approve the results. Then I download the image and apply\n\n2) Python script to run postprocessing\n\nThis workflow is good for few projects and few relatively-savy users but as time passes projects pile up and team grows. At the moment, there are several different tasks, each needs a bit different posprocessing and more and more people working with it.\n\n**Do you know any software that can help me to implement this workflow without manually showeling data from CVAT to scripts?** \n\nI looked around if it's possible to extend CVAT but it's meant as annotation tool not a link in a production chain so I didn't found anything (appart plugging my own models into it). As an alternative I was thinking about writing my own solution. I would be able to write a backend but I cannot write the frontend part. I don't know javascript and searching through github for any decent frontend supporting tools (like brushes for segmentation) and label handling(fix mislabeled stuff etc)   led nowhere so I gave up thinking about it.",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-16",
  "username_encoded": "Z0FBQUFBQm5Lakwzd2VmWXFNWm94NUs0MWhXWkRGOXN6Skw5M01HcmxXN3RJZzRlR3BuNjZORjJud005RFF5Y0drMlNfQzBYelB4bWV2Skw2YU5qM1JHZFZ2ZEp6M3hqQVE9PQ==",
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