I have trained my own model using tensorflow (https://github.com/tensorflow/models/tree/master/research/object_detection) to identify objects in images. I am testing this model using Google object detection API
My question is the way Google coded the ipython notebook is to output image which has size 200 kb to 300 kb output size, the link to this ipythonnotebook(https://github.com/tensorflow/models/blob/master/research/object_detection/object_detection_tutorial.ipynb.)
How do I output images with orignal size (which is 15MB) (I am running this code on my local machine). Ive tried changing Helper Code session of the notebook it didnt work. Anything that I am missing here?
def load_image_into_numpy_array(image):
(im_width, im_height) = image.size
return np.array(image.getdata()).reshape(
(im_height, im_width, 3)).astype(np.uint8)
In the detection part of ipython notebook I changed image size to
IMAGE_SIZE = (120, 80)
It did the trick