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project/project_proposal.md

@@ -21,7 +21,7 @@
     - some fruits are peeled, cut in half or in slices
     - :sparkles: the dataset is much cleaner than other fruit datasets we found on Kaggle, which often contain images of cooked food or fruit juices (e.g. [here](https://www.kaggle.com/datasets/yudhaislamisulistya/plants-type-datasets))
   
-![Bananas in different stages and quantities](figures/bananas-different-stages.png)
+![Bananas in different stages and quantities](figures/examples_from_dataset/bananas-different-stages.png)
   
 - we will narrow the dataset down to **30 types of fruits**
   - **29430** images
@@ -43,7 +43,7 @@
 - 260 x 380 pixels in example image
 - => 1D vector with length 260 x 380 x 3 = 296,400
 
-![Example image](figures/banana.jpg)
+![Example image](figures/examples_from_dataset/banana.jpg)
   
 | | Pixel 1 | Pixel 2 | Pixel 3 | ... | Pixel 381 (=second row) | ... | Pixel height x width = 98,800 |
 | --- | --- | --- | --- | --- | --- | --- | --- |
@@ -67,7 +67,7 @@
 - first ideas are: 
   - reduce the size of the images
   - **edge detection** (because next to the colour, the shape of the fruit object is important)
-  - ![Banana with detected edges](figures/banana-edges.jpg)
+  - ![Banana with detected edges](figures/examples_from_dataset/banana-edges.jpg)
   - concatenating edge detection with RGB values
     
 ## Which algorithms can solve our task?