Row 2198

Row ID: 2198 | Dataset Entry | Axioma AXP Content Repository

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I have a dataset of images (two class) stored locally on my pc I want to train on. When I load from my hard drive using the flow\_from directory function I get a much smoother loss curve which is more desireable for me however this is very slow. I have discovered that loading the data into ram first by using cv2 to load the data into numpy arrays makes the training so much faster (almost 3x). however now the loss curve is the same general shape but has many spikes and is very jagged and makes my accuracy worse. I assume this has something to do with a difference in processing of the images as they are loaded. What should I change about my numpy loading to make it more like the flow\_from\_directories function.

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https://preview.redd.it/l1bg6r51rybb1.png?width=716&format=png&auto=webp&s=501f98b9006073592b620780b6f97d4553e290e9

https://preview.redd.it/zeuh7t51rybb1.png?width=1735&format=png&auto=webp&s=d81589cf46f0795e19972d2128cfcdf97680bd97

FieldValue
text I have a dataset of images (two class) stored locally on my pc I want to train on. When I load from my hard drive using the flow\_from directory function I get a much smoother loss curve which is more desireable for me however this is very slow. I have discovered that loading the data into ram first by using cv2 to load the data into numpy arrays makes the training so much faster (almost 3x). however now the loss curve is the same general shape but has many spikes and is very jagged and makes my…
label r/tensorflow
dataType post
communityName r/tensorflow
datetime 2023-07-14
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Raw Record

{
  "text": " I have a dataset of images (two class) stored locally on my pc I want to train on. When I load from my hard drive using the flow\\_from directory function I get a much smoother loss curve which is more desireable for me however this is very slow. I have discovered that loading the data into ram first by using cv2 to load the data into numpy arrays makes the training so much faster (almost 3x). however now the loss curve is the same general shape but has many spikes and is very jagged and makes my accuracy worse. I assume this has something to do with a difference in processing of the images as they are loaded. What should I change about my numpy loading to make it more like the flow\\_from\\_directories function. \n\n​\n\n​\n\nhttps://preview.redd.it/l1bg6r51rybb1.png?width=716&format=png&auto=webp&s=501f98b9006073592b620780b6f97d4553e290e9\n\nhttps://preview.redd.it/zeuh7t51rybb1.png?width=1735&format=png&auto=webp&s=d81589cf46f0795e19972d2128cfcdf97680bd97",
  "label": "r/tensorflow",
  "dataType": "post",
  "communityName": "r/tensorflow",
  "datetime": "2023-07-14",
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