In this case, we already had the bbox coordinates with us,
What would be the way to generate them on a personalized dataset?
I think (not sure ) it can be done using the V1 cmap technique, and get the dimensions from the cmap region or its done using Image Segmentation?
In short, the following 4 parameters (x1, y1, x2, y2) is what we are training for and trying to predict for the validation set !
Somebody who knows better, please correct me here if I’m wrong.
Yes, but we only use them for the training set. And, we compare/validate them for the validation set. Hope that clarifies.
Completely forgot about validation and test sets…
My bad…
It all makes sense now…
Thanks for replying
Hi @ecdrib. I have the same problem. Will you share your understanding?
I am also very interested to try pytorch/fastai on windows.
Haven’t try it yet, but this is seems what you are looking for :
Howto: installation on Windows
Then what’s the loss function or the metric involved then?
Is it Area of the two boxes then?
This is my current understanding,
I am still trying to understand the code and it’s working properly, but what he said makes sense that we verify the bbox cor with the original ones by predicting them on the given dataset,(so we need to train them accordingly)
And probably using area , or ecludiean distance or something as a metric to calculate the error involved in the same
Drawing a bbox is easy as we just need to pass the coordinates just like Jeremy had shown as in the nbs
The main thing is to detect the object in the given image as there can be multiples of the same type…
Hope someone will correct me in my understanding
I’ll have to rewatch the lectures later today / look at the notebook to give an exact answer.
But, I think might be on the right track there. (probably more like some loss function on each feature/class) Perfect time to open the notebook and read some code. 
Can someone tell about how to use open_image(). I am getting this type error from pathlib.py (TypeError: expected str, bytes or os.PathLike object, not dict) . I’ve tried typecasting but it is not working out ?
what are you passing? Looks like a dictionary.
Yes Thank you
I tried with this, open_image(IMG_PATH/im0_d[FILE_NAME]) . I tried typecasting as well, it’s not working .
Just paste IMG_PATH/im0_d[FILE_NAME] in a cell and see what it is. Then paste type(IMG_PATH/im0_d[FILE_NAME]) in a cell and see what that is. I haven’t run the code yet so don’t know off the top of my head.
For PyCharm and Mac users - a list of the shortcuts Jeremy provided for Visual Studio Code.
Action (PyCharm + Mac shortcut)
Command palette- (Shift + Command + A)
Select interpreter (for fastai env) - (Shift+Command+A) and then look for “interpreter”
Select terminal shell- (Shift+Command+A) and then look for “terminal shell”
Go to symbol (Option + Command + O)
Find references (Command+ G)(go down in the references) (Command + Shift + G) (go up)(Command + Function + F7) (look for all)
Go to definition (Command + Down Arrow Key)
Go back (Command + [ )
View documentation ( Option + Space) for viewing source and (Function + F1) for viewing documentation
Hide sidebar (Command + 1) redoing it will bring it back
Zen mode (Control + Command + F) and same to get out too.
Find them all with the (Shift + Command+ A) palette option for reference.
Probably not the best list (would love suggestions) and perhaps should create a new thread for it too. Just wanted to leave myself a note. Didn’t use symbols/shorthand for keys because I had trouble with them as a new Mac user once when I didn’t use shortcuts.
I tried with IMG_PATH/im0_d[FILE_NAME] , it gives the same error.
You will have to give more information than this. Exact Input/Exact Output otherwise it’s not possible to help. Read http://wiki.fast.ai/index.php/How_to_ask_for_Help
This is awesome, thanks! I’ve been using PyCharm and thought I should find the equivalents (especially “Go back”). Thanks for taking the time to write this up.
If you need to typeset some pretty math:
$\alpha$ becomes \alpha (now it works in Discourse too).what is the output of im0_d[FILE_NAME]?