Row 7411

Row ID: 7411 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 7411 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Hello,

I need advice on how to move on with my project, Initially I wanted to create a face recognition system. I first gathered a dataset of celebrity faces with 99 classes and about 16k total images and fine-tuned ConvNeXtTiny model on the dataset using tensorflow and got a result of 93% accuracy. Now this is technically only an image classification application where it can tell the faces apart and tell which celebrity it is. However, I need to extened this project to a fully face recognition system.

How can I use tensorflow transfer learning with existing models to make this system full circle? Basically I need a face detection model that is compatible with tensorflow 2.15.0 then preprocess the faces(Either from a webcam or can be processed from an unknown dataset) then passing them to the ConvNeXt model for recognition. my Idea is that the unknown faces would be registered and added to the dataset.

I have done some research and tried to implement VGGFACE but I was met with so many errors that i couldn't go forward with it because apparently VGGface isnt compatible with tensorflow 2.x >.

I need recommendations and guidance on how to move forward and integrate a model with my face image classifier model. are there any resources that can be implemented easily with tensorflow ? And how easy or hard is this task to complete?

FieldValue
text Hello, I need advice on how to move on with my project, Initially I wanted to create a face recognition system. I first gathered a dataset of celebrity faces with 99 classes and about 16k total images and fine-tuned ConvNeXtTiny model on the dataset using tensorflow and got a result of 93% accuracy. Now this is technically only an image classification application where it can tell the faces apart and tell which celebrity it is. However, I need to extened this project to a fully face recognition…
label r/deeplearning
dataType post
communityName r/deeplearning
datetime 2024-05-16
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url_encoded Z0FBQUFBQm5Lak9IOExTN3UwRzctZExJOTdsbVp6b2hBWEIxVmgzdFZ4SHJCNnVMQ2d3YWhxejVpbk1PYnQyYkpHUC1DTFhGc2ZFSkg4R2NzTm9PTkJfc3FKa201eHdxMkxVUjZFbml4X0lXVHh6SklKRjd1ZDRoVVJBdmxDSlU5a08wWTVTWHlwV2U4R0syamJBVzk1NnpONUl5WVJiYWpTUllaVkJmNEE0MHA5UWVjZ01BWW4yazRaTGIwQ25PUkVvMGZ6QTFhSUNRUGQzMENfNWNZSFRSbktzZVpKdXNVZz09

Raw Record

{
  "text": "Hello,\n\nI need advice on how to move on with my project, Initially I wanted to create a face recognition system. I first gathered a dataset of celebrity faces with 99 classes and about 16k total images and fine-tuned ConvNeXtTiny model on the dataset using tensorflow and got a result of 93% accuracy. Now this is technically only an image classification application where it can tell the faces apart and tell which celebrity it is. However, I need to extened this project to a fully face recognition system.\n\nHow can I use tensorflow transfer learning with existing models to make this system full circle? Basically I need a face detection model that is compatible with tensorflow 2.15.0 then preprocess the faces(Either from a webcam or can be processed from an unknown dataset) then passing them to the ConvNeXt model for recognition. my Idea is that the unknown faces would be registered and added to the dataset.\n\nI have done some research and tried to implement VGGFACE but I was met with so many errors that i couldn't go forward with it because apparently VGGface isnt compatible with tensorflow 2.x >.\n\nI need recommendations and guidance on how to move forward and integrate a model with my face image classifier model. are there any resources that can be implemented easily with tensorflow ? And how easy or hard is this task to complete?",
  "label": "r/deeplearning",
  "dataType": "post",
  "communityName": "r/deeplearning",
  "datetime": "2024-05-16",
  "username_encoded": "Z0FBQUFBQm5LakwzUWo5LWF4M3JRWlJza2hNTzc1eFZZeGdRQTdmdGFMTHN0RHNwRDl3VXNTY3UxSUVHNk5aM09zS1pIdE9obklTV2JNM3Q4NTM3X0J4VjNxTHNkNVdBY1JaVE0zNUdSV21TeWxDY1hlRGg3cjA9",
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Entry Information