Keyword consistency about chainercv HOT 10 OPEN

I think it is better to unify keywords. I guessed current rules from the codes.

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@yuyu2172 How do think of it? Do you know other implicit rules?

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Thanks for summarizing this.
I have no complaint for everything, but the second one. I think we were discussing on the usage of cls inside eval_detection. I think this is under discussion.

Other than that, here are some that I came up.

• For a name of a function or a class, image is used. As a name of a variable inside a function, img is used.
• In extensions, models are named as target.

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@yuyu2172 thank you. I merged the rules you suggested. I changed the state of usage of class to "under discussion".

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Copied from #163, these are rules for bounding boxes.

• bb is a (R,)
• bbox is a (R, 4)
• bboxes is a (B, R, 4) or list of (R_i, 4) i=1, ..., B.
• rois is a (R', 4) which consists of bounding boxes for multiple images. Assuming that there are B images each containing R_i bounding boxes, R' = \sum R_i. rois comes together with a (R',) array called batch_indices, which contains batch indices of images to which bounding boxes correspond to.

For images, a similar rule applies like below.

• img is a (C, H, W).
• imgs is a (B, C, H, W) or a list of (C, H, W).

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@yuyu2172 Thank you. I merged them.

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I think there is another rule.

• x is a variable whose shape can be inferred from context. It can be used only when there is no confusion on its shape.

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I think this naming conventions should be included in the documentation.

Here are some rules I found used in ChainerCV.

• prob is used for probability. If this indicates multi-class probability, cls_prob is also acceptable. For convenience cls_ can be omitted.
• roi_nouns represents values associated to rois. The shape is (R', ...).
  • In the case when the batchsize=1, variables can be renamed as noun = roi_nouns.

Rules specific to instance segmentation should also be documented.

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I think this naming conventions should be included in the documentation.

👍

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Another rule

• cls_nouns is a multi-class version of nouns.
  • ex: cls_locs is (B, R, L, 4) and locs is (B, R, 4).

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