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1. how many horses are there ? the two in the photo are clearly distinguishable.
2. no worries, (people) recognition on 500 images can be done in millisecs. you can probably use any old beast you got.
3. that's a different topic/problem (and might need seperate tratment), no ?
4. yes usually recognition improves with image count. but again, it depends on the horse count, and on how easy they're seperable. start to collect pics from the feeders position, i guess.

1. how many horses are there ? the two in the photo are clearly distinguishable.
2. no worries, (people) recognition on 500 images can be done in millisecs. you can probably use any old beast you got.
3. that's a different topic/problem (and might need seperate tratment), treatment), no ?
4. yes yes, usually recognition improves with image count. but again, it depends on the horse count, and on how easy they're seperable. start to collect pics from the feeders position, i guess.

1. how many horses are there ? the two in the photo are clearly distinguishable.
2. no worries, (people) recognition on 500 images can be done in millisecs. you can probably use any old beast you got.

3. that's a different topic/problem (and might need seperate treatment), no ?

   but it might work, if you add some dog pics, and have a 'dog' class and some raccoon pica and a 'racoon class'

4. yes, usually recognition improves with image count. but again, it depends on the horse count, and on how easy they're seperable. start to collect pics from the feeders position, i guess.

1. how many horses are there ? the two in the photo are clearly distinguishable.
2. no worries, (people) recognition on 500 images can be done in millisecs. you can probably use any old beast you got.

3. that's a different topic/problem (and might need seperate treatment), no ?

   but a. it might work, if you add some dog pics, and have a 'dog' class 'not-a-horse' class, with pics of blue sky, dog,raccoon, and whatnot. b. you might train some raccoon pica and a 'racoon class'general horse(head) 'detector' (like in horse-or-not), (that's what @sturkmen was trying to hint at.)

4. yes, usually recognition improves with image count. but again, it depends on the horse count, and on how easy they're seperable. start to collect pics from the feeders position, i guess.guess. if your animals are that easy to seperate, like in the pic above, a handful of images will do for sure.

1. how many horses are there ? the two in the photo are clearly distinguishable.
2. no worries, (people) recognition on 500 images can be done in millisecs. you can probably use any old beast you got.

3. that's a different topic/problem (and might need seperate treatment), no ?

   a. it might work, if you have a 'not-a-horse' class, with pics of blue sky, dog,raccoon, and whatnot. whatnot.

   b. you might train some general horse(head) 'detector' (like in horse-or-not), similar to the face detection (that's what @sturkmen was trying to hint at.)

4. yes, usually recognition improves with image count. but again, it depends on the horse count, and on how easy they're seperable. start to collect pics from the feeders position, i guess. if your animals are that easy to seperate, like in the pic above, a handful of images will do for sure.

last, but not least - might be, that using opencv's face-reco framework is way overkill for this job. you might start with comparing the (grayscale) image via cv::norm() to some pics on disk, and take the one with the shortest distance.

1. how many horses are there ? the two in the photo are clearly distinguishable.
2. no worries, (people) recognition on 500 images can be done in millisecs. you can probably use any old beast you got.

3. that's a different topic/problem (and might need seperate treatment), no ?

   a. it might work, if you have a 'not-a-horse' class, with pics of blue sky, dog,raccoon, and whatnot.

   b. you might train some general horse(head) 'detector' (like in horse-or-not), to go in front of the 'recognition' pass similar to the face detection (that's what @sturkmen was trying to hint at.)

4. yes, usually recognition improves with image count. but again, it depends on the horse count, and on how easy they're seperable. start to collect pics from the feeders position, i guess. if your animals are that easy to seperate, like in the pic above, a handful of images will do for sure.

last, but not least - might be, that using opencv's face-reco framework is way overkill for this job. you might start with comparing the (grayscale) image via cv::norm() to some pics on disk, and take the one with the shortest distance.