latest bitsnbytes model trained on GOCO (4-27-24)

yolov5-based detection model for use detecting common food items in broad categories

GroceryInContext.yaml

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+# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
+path: ./  # dataset root dir
+train: images/train  # train images (relative to 'path') 128 images
+val: images/train  # val images (relative to 'path') 128 images
+test:  # test images (optional)
+
+names:
+  0: box
+  1: bottle
+  2: pouch
+  3: cylinder
+  4: book

bitsnbytes.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:efd993646bcfb8adb09b0f68e131b1c0321cd05d6acab5d218b9cd7a97b06dcf
+size 14444776