<p><strong>Initial note:</strong> Since you talk about having "created a simple model" and having said model "identify this image as car", I'll assume you're not actually using a model for object detection, but one that does simple classification.</p>

<p>The problem you're trying to solve is a different problem than the one you trained your network to solve.</p>

<p>You have a network that was trained to tell you <strong>whether an image you feed to it contains a car</strong>. This is a classification problem.</p>

<p>What you want now is <strong>the area where the car actually is in the image</strong>. This is a much harder problem to solve, because now your network doesn't need to output anymore "I see a car" vs. "I don't see a car", but instead, in the <strong>simplest</strong> formulation, "I see a car in the rectangle (x,y,w,h)". In another formulation, more similar to what your desired output would be, you would have <strong>per <em>each pixel</em> a classification like "it's a car" or "not a car"</strong>. These problems are then object <em>detection</em> and <em>segmentation</em>.</p>

<p>There are studies out there that tackle these problems (<a href="https://arxiv.org/abs/1504.08083" rel="nofollow noreferrer">one example</a> and <a href="https://people.eecs.berkeley.edu/~jonlong/long_shelhamer_fcn.pdf" rel="nofollow noreferrer">another</a>), but my suggestion is to have a look at Tensorflow's <a href="https://github.com/tensorflow/models/tree/master/research/object_detection" rel="nofollow noreferrer">object detection API</a> which have pretrained models you might exploit for your use-case.</p>
How to get the identified area from tensor flow?
<p>I have created a simple model in TF to identify cars.
it identified the bellow image as a car:</p>

<p><a href="https://i.stack.imgur.com/1POkv.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/1POkv.jpg" alt="enter image description here"></a></p>

<p>What I would like to have is the area(or crop of the area) of the actual identified car as follows:
<a href="https://i.stack.imgur.com/HuJzm.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/HuJzm.jpg" alt="enter image description here"></a></p>

<p>any ideas if it is possible with Tensorflow? my current python code is looking like that:</p>

<pre><code>file_name = 'mustangTest.png'
input_height = 299
input_width = 299
input_mean = 0
input_std = 255
input_layer = "Mul"
output_layer = "final_result"
t = read_tensor_from_image_file(src,input_height=input_height,input_width=input_width,input_mean=input_mean,input_std=input_std)
        input_name = "import/" + input_layer
        output_name = "import/" + output_layer
        input_operation = graph.get_operation_by_name(input_name);
        output_operation = graph.get_operation_by_name(output_name);

        with tf.Session(graph=graph) as sess:
            results = sess.run(output_operation.outputs[0],{input_operation.outputs[0]: t})
            results = np.squeeze(results)
        top_k = results.argsort()[-5:][::-1]
        print("car is " + top_k[0]")
</code></pre>