How do we tell our program what we want to look for?
I created a directory full of positive images (images that contain the object(s) that I want to identify) and I created a directory full of images that I know do not contain any of the objects that I want to identify. My positive image count was about 1134 and my negative image count was about 625. In all other posts and papers I have read it seems that the more images you have the better coverage you get on the differences in such things as scale, orientation, distortion.
But you also have to take into account if you have over 1000 images you will have to sit through and mark every one of those images with boxes identifying the objects and positions in each image and this can be really time consuming. You may ask surely there is a way of automating this? But if this was automated then you would already have the exact thing you are trying to make in the first place… 🙂
So sit back and get comfortable because you could be there for awhile. So is it better to spend the time up front and the program execute and identify fast, or have a program take forever identifying objects at run time? Guess its all about what you want/need from your implementation.
To run the ObjectMarker executable
ObjectMarker.exe <outputfile> <directory of jpg images to mark>
ObjectMarker in Action
Once you are done marking all the images you should have a new output file that its contents should look something like this
filename <no. of objects marked in the image> <top left corner x-coordinate> <top left corner y-coordinate> <width of rectangle> <height of rectangle>
20100627_001220_1024_0193.jpg 1 705 127 22 6
20100627_002044_1024_0193.jpg 1 705 127 58 62
20100627_004432_1024_0193.jpg 1 715 135 48 54
20100627_005956_1024_0193.jpg 1 715 135 46 54
20100627_010132_1024_0193.jpg 1 712 132 49 57
20100627_011308_1024_0193.jpg 1 721 144 37 40
20100627_014044_1024_0193.jpg 1 720 142 40 49
20100627_015444_1024_0193.jpg 1 705 137 63 59
20100627_015956_1024_0193.jpg 1 707 136 66 60
20100627_021220_1024_0193.jpg 1 711 137 58 54
20100627_021932_1024_0193.jpg 1 704 137 66 56
20100627_025432_1024_0193.jpg 1 699 136 69 55
20100627_031156_1024_0193.jpg 1 695 141 77 52
20100627_032208_1024_0193.jpg 1 699 137 73 53
20100901_010108_1024_0193.jpg 2 761 799 93 94 803 216 34 44
Tags: Haar Classifier