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Copy pathvgg_uploaded-images.txt
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vgg_uploaded-images.txt
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Command Line Arguments:
dir = uploaded_images/
arch = vgg
dogfile = dognames.txt
Pet Image Label Dictionary has 4 key-value pairs.
Below are 4 of them:
1 key: bedlington_terrier_01.jpg label: bedlington terrier
2 key: Tiger_01.jpg label: tiger
3 key: bedlington_terrier_02.jpg label: bedlington terrier
4 key: white_bread_01.jpg label: white bread
MATCH:
bedlington_terrier_01.jpg:
Real: bedlington terrier Classifier: bedlington terrier
Tiger_01.jpg:
Real: tiger Classifier: tiger panthera tigris
bedlington_terrier_02.jpg:
Real: bedlington terrier Classifier: bedlington terrier
NOT A MATCH:
white_bread_01.jpg:
Real: white bread Classifier: french loaf
# Total Images 4 # Matches: 3 # NOT Matches: 1
MATCH:
bedlington_terrier_01.jpg:
Real: bedlington terrier Classifier: bedlington terrier
PetLabelDog: 1 ClassLabelDog: 1
Tiger_01.jpg:
Real: tiger Classifier: tiger panthera tigris
PetLabelDog: 0 ClassLabelDog: 0
bedlington_terrier_02.jpg:
Real: bedlington terrier Classifier: bedlington terrier
PetLabelDog: 1 ClassLabelDog: 1
NOT A MATCH:
white_bread_01.jpg:
Real: white bread Classifier: french loaf
PetLabelDog: 0 ClassLabelDog: 0
# Total Images 4 # Matches: 3 # NOT Matches: 1
** Statistics from calculates_results_stats() function:
N Images: 4 N Dog Images: 2 N NotDog Images: 2
Pct Corr dog: 100.0 Pct Corr NOTdog: 100.0 Pct Corr Breed: 100.0
** Check Statistics - calculated from this function as a check:
N Images: 4 N Dog Images: 2 N NotDog Images: 2
Pct Corr dog: 100.0 Pct Corr NOTdog: 100.0 Pct Corr Breed: 100.0
Summary results for the model VGG
Number of images: 4
Number of Dog Images: 2
Number of "Not-a" Dog Images: 2
Pct Match : 75.0
Pct Correct Dogs : 100.0
Pct Correct Breed : 100.0
Pct Correct Notdogs : 100.0
** Total Elapsed Runtime: 0:0:13