hello guys,
I am currently using this 27 pre-trained code example to train my own dataset. My dataset classes have postures of humans like sitting and standup. I use resnet18 model for this.
As limitations, I have very few train images (15 at most) to test it.(will add more obv.) and I changed minor parts of the main.py like changing scale() to resize() because they were deprecated. In the run time it says Prec1,5 not working but code runs anyway.
The problem is I used the some of the same images in “val” or compeletely irrelevant ones to observe the loss/acc change.
edit: the images have 224x224 px size.
This was what I got: (compeletly irrelevant pics like birds in val)
Epoch: [89][0/1]        Time 2.153 (2.153)      Data 2.114 (2.114)      Loss 0.6270 (0.6270)    Prec@1 72.727 (72.727)  Prec@5 100.000 (100.000)
Test: [0/1]     Time 1.863 (1.863)      Loss 0.7864 (0.7864)    Prec@1 50.000 (50.000)  Prec@5 100.000 (100.000)

Prec@1 50.000 Prec@5 100.000

Question is: If I add relevant 1000+ imgs to my “train” and x-amount to “val”. will it have different and proper results? Therefore, can I use it? Or should I scrap it and write my own as it is wrong/deprecated?