Row 2127

Row ID: 2127 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 2127 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Hello everyone,

probably a very noob question, I'm just started in this new magic worl of AI and ML. I've run every tutorial project I could find, i develop my own Dog or Cat model by transfering from MobileNet. I'm now struggling with the classification of documents.

I have 50 companies that sends us invoices and I want to train a model in order to recognize which company sent us the invoice automatically. The document structure is basically the same (some minor differences in the structure of a table) the main difference lies in the logo of the company of course. The images are very large, so what I'm trying right now is this:

(using Tensorflow.js if it metters)

https://preview.redd.it/sx7ipq7zqt8b1.png?width=816&format=png&auto=webp&s=5e39fc3e252f4b46ce0b80cee1741d6623a6c27a

This the network i thought it could work.

I process every image in this way:

https://preview.redd.it/2nbdif88rt8b1.png?width=681&format=png&auto=webp&s=7fe5ec1221f9227c5892cc2af99bd34df6938654

Then i try to train the model with this code:

https://preview.redd.it/ysiakhynrt8b1.png?width=711&format=png&auto=webp&s=4212fcfbff972a5ab1a2c652b95970f10916a367

But at this point the log tells me that it will not reach 0.4 as accuracy.

Can you point me in the right direction?

FieldValue
text Hello everyone, probably a very noob question, I'm just started in this new magic worl of AI and ML. I've run every tutorial project I could find, i develop my own Dog or Cat model by transfering from MobileNet. I'm now struggling with the classification of documents. I have 50 companies that sends us invoices and I want to train a model in order to recognize which company sent us the invoice automatically. The document structure is basically the same (some minor differences in the stru…
label r/tensorflow
dataType post
communityName r/tensorflow
datetime 2023-06-28
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Raw Record

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  "text": "Hello everyone,\n\nprobably a very noob question, I'm just started in this new magic worl of AI and ML. I've run every tutorial project I could find, i develop my own Dog or Cat model by transfering from MobileNet.   \nI'm now struggling with the classification of documents.   \n\n\nI have 50 companies that sends us invoices and I want to train a model in order to recognize which company sent us the invoice automatically. The document structure is basically the same (some minor differences in the structure of a table) the main difference lies in the logo of the company of course.   \nThe images are very large, so what I'm trying right now is this:  \n\n\n(using Tensorflow.js if it metters)   \n\n\nhttps://preview.redd.it/sx7ipq7zqt8b1.png?width=816&format=png&auto=webp&s=5e39fc3e252f4b46ce0b80cee1741d6623a6c27a\n\nThis the network i thought it could work.  \n\n\nI process every image in this way:  \n\n\nhttps://preview.redd.it/2nbdif88rt8b1.png?width=681&format=png&auto=webp&s=7fe5ec1221f9227c5892cc2af99bd34df6938654\n\nThen i try to train the model with this code:  \n\n\nhttps://preview.redd.it/ysiakhynrt8b1.png?width=711&format=png&auto=webp&s=4212fcfbff972a5ab1a2c652b95970f10916a367\n\nBut at this point the log tells me that it will not reach 0.4 as accuracy.   \n\n\nCan you point me in the right direction?",
  "label": "r/tensorflow",
  "dataType": "post",
  "communityName": "r/tensorflow",
  "datetime": "2023-06-28",
  "username_encoded": "Z0FBQUFBQm5LakwwMVZGeDhxVVhFOHV3WkFnV2pFaG9aNXVlRHdKWmRZaC1JQlU2YnV6TlVORGNPSnpUUmlqakJTRFF3LVhpMl9sX3h1NWZwazN0SkVySjdMRVZROGdoa3c9PQ==",
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}
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