Image Identify using machine learning in Python.

#pip install imageai

#pip install Tensorflow

#pip install keras

from imageai.Prediction import ImagePrediction

import os

from keras.models import load_model

Givenimage="picc.jpg"

execution_path=os.getcwd()

#print(execution_path)

prediction = ImagePrediction()

prediction.setModelTypeAsSqueezeNet()

prediction.setModelPath(os.path.join(execution_path, "squeezenet_weights_tf_dim_ordering_tf_kernels.h5"))

prediction.loadModel()

predictions, probabilities = prediction.predictImage(os.path.join(execution_path, Givenimage), result_count=3 )

for eachPrediction, eachProbability in zip(predictions, probabilities):

    print(eachPrediction , " : " , eachProbability) 

Result:

WARNING:tensorflow:11 out of the last 11 calls to <function Model.make_predict_function.<locals>.predict_function at 0x7f941e211598> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for more details. lion : 99.9810516834259 brown_bear : 0.004735136099043302 Airedale : 0.004706834806711413

## Programme is 99.98 % sure that it was Lion , Thats Great!

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