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author | nunzip <np.scarh@gmail.com> | 2019-02-12 20:13:37 +0000 |
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committer | nunzip <np.scarh@gmail.com> | 2019-02-12 20:13:37 +0000 |
commit | c5c3e922a951c29c66d6377b5fea25189a25b85c (patch) | |
tree | 98014889de2e3a95b33580dae1a2b1165a1e5919 | |
parent | 4046ef55a352bdfaa238f0499a280f4844c705f0 (diff) | |
download | e4-vision-c5c3e922a951c29c66d6377b5fea25189a25b85c.tar.gz e4-vision-c5c3e922a951c29c66d6377b5fea25189a25b85c.tar.bz2 e4-vision-c5c3e922a951c29c66d6377b5fea25189a25b85c.zip |
Remove 2pixels testimode
-rwxr-xr-x | evaluate.py | 13 |
1 files changed, 0 insertions, 13 deletions
diff --git a/evaluate.py b/evaluate.py index 321e792..fb72a8b 100755 --- a/evaluate.py +++ b/evaluate.py @@ -50,10 +50,6 @@ def make_histogram(data, model, args): leaves = np.apply_along_axis(np.bincount, axis=0, arr=leaves, minlength=args.leaves) histogram[i][j] = leaves.reshape(hist_size) - print(histogram[0][0].shape) - plt.bar(np.arange(100), histogram[0][0].flatten()) - plt.show() - return histogram def run_model (data, train, test, train_part, args): @@ -123,15 +119,6 @@ def main(): print("Accuracy: ",acc[i][j]) args.seed = 1 - plt.plot(a,acc[0]) - acc[1][2]+=0.01 - acc[1][4]+=0.01 - acc[1][7]+=0.01 - acc[1][8]+=0.01 - acc[1][9]+=0.01 - acc[1][10]+=0.01 - acc[1][12]+=0.01 - acc[1][14]+=0.01 plt.plot(a,acc[1]) plt.legend(('Axis aligned','Two Pixels Test'), loc='best') plt.ylabel('Normalized Classification Accuracy') |