Regarding image classification using CNN
Besides that, probably your training set has way easier images than your test set (those image that you give manually). That can happen even if you are feeding the network from the same dataset.
To have better results on unseen images, you must have to reach a good generalisation level. Try what is said previously above...
I built a image classification model using convolutional neural network for 5 classes.It is giving the training accuracy as 100% and testing accuracy as 82%. But when I gave an image manually for predicting, the model is not able to classify them correctly.For 10 images the model is classifying only 3-4 images correctly.What is the mistake? What should I do??