Error in who_is_it

Course Q&A Deep Learning Specialization Convolutional Neural Networks
1

I have successfully submitted my assignment and I haven’t found any errors. But still I see the message that there was an error in the “who_is_it” after submission.

def who_is_it(image_path, database, model):
“”"
Implements face recognition for the office by finding who is the person on the image_path image.

Arguments:
    image_path -- path to an image
    database -- database containing image encodings along with the name of the person on the image
    model -- your Inception model instance in Keras

Returns:
    min_dist -- the minimum distance between image_path encoding and the encodings from the database
    identity -- string, the name prediction for the person on image_path
"""

### START CODE HERE

## Step 1: Compute the target "encoding" for the image. Use img_to_encoding() see example above. ## (≈ 1 line)
encoding =  img_to_encoding(image_path, model)

## Step 2: Find the closest encoding ##

# Initialize "min_dist" to a large value, say 100 (≈1 line)
min_dist = 100

# Loop over the database dictionary's names and encodings.
for (name, db_enc) in database.items():
    
    # Compute L2 distance between the target "encoding" and the current db_enc from the database. (≈ 1 line)
    dist = np.linalg.norm(encoding-db_enc)

    # If this distance is less than the min_dist, then set min_dist to dist, and identity to name. (≈ 3 lines)
    if dist<min_dist:
        min_dist = dist
        identity = name
### END CODE HERE

if min_dist>0.7:
    print("Not in the database.")
else:
    print ("it's " + str(identity) + ", the distance is " + str(min_dist))
    
return min_dist, identity

image
image1079×507 53.8 KB

After submission:
Code Cell UNQ_C1: Function ‘triplet_loss’ is correct.
Code Cell UNQ_C2: Function ‘verify’ is correct.
Code Cell UNQ_C3: Unexpected error (TypeError("’>’ not supported between instances of ‘NoneType’ and ‘float’")) occurred during function check. We expected function who_is_it to return compute_layer_style_cost test 1 failed. Please check that this function is defined properly.
If you see many functions being marked as incorrect, try to trace back your steps & identify if there is an incorrect function that is being used in other steps.
This dependency may be the cause of the errors.

2

Did you save your notebook before you submitted it for grading?

3

Have you re-named your notebook .ipynb file?

4

Hi @ChandiniSaiKumarDukk,

The error would have been shown in the unit tests as well. I am not sure why might be happening.
One possible reason might be as @TMosh said: maybe you had not submitted the latest saved file.

5

Thank you @TMosh @thearkamitra for your reply
I have figured why that is happening it is since I haven’t assigned any value for identity when I assigned the value to 0 the problem has been fixed.

6

I’m afraid that is a very wrong solution.
The ‘name’ and ‘identity’ values comes from these statements:

for (name, db_enc) in database.items():

and inside the for-loop and if-statements:
identity = name

You do not have to set ‘identity’ yourself. And forcing it to zero is not a good idea, because it’s only going to work in one specific instance.

7

Thank you @TMosh for your reply
I have initialized the value of identity =0 before the for loop, whereas I have maintained the value of identity= name in the for loop.

8

Thanks for your explanation.

I think your solution is not necessary, because if min_dist is initialized to an impossibly large value, then “identity” will be set to “name” on the first pass through the for-loop.

This should prevent “identity” from being undefined when the function returns.

In any case, setting identity = 0 as a default value is a poor choice, because “name” is a text string, and 0 is a number. So it is initializing identity to the wrong data type. Using a null string would be a better idea.