Python OverfeatTransformer.predict Examples

Example #1

File: plot_localization_tutorial.py Project: Faruk-Ahmed/sklearn-theano

# Show all the boxes being processed
axarr[0, 2].imshow(X)
axarr[0, 2].axis('off')
clf = OverfeatTransformer(force_reshape=False)
X_tf = clf.transform(X)
x_points = np.linspace(0, X.shape[1] - 231, X_tf[0].shape[3])
y_points = np.linspace(0, X.shape[0] - 231, X_tf[0].shape[2])
xx, yy = np.meshgrid(x_points, y_points)
for x, y in zip(xx.flat, yy.flat):
    axarr[0, 2].add_patch(Rectangle((x, y), 231, 231, fc='yellow', ec='black',
                          alpha=.4))

# Get all points with sloth in the top 5 labels
sloth_label = "three-toed sloth, ai, Bradypus tridactylus"
clf = OverfeatLocalizer(match_strings=[sloth_label])
sloth_points = clf.predict(X)[0]
axarr[1, 0].imshow(X)
axarr[1, 0].axis('off')
axarr[1, 0].autoscale(enable=False)
axarr[1, 0].scatter(sloth_points[:, 0], sloth_points[:, 1], color='orange',
                    s=50)

# Final localization box
sloth_box = convert_points_to_box(sloth_points, 'orange', .6)
axarr[1, 1].imshow(X)
axarr[1, 1].autoscale(enable=False)
axarr[1, 1].add_patch(sloth_box)
axarr[1, 1].axis('off')

# Remove the unused box
axarr[1, 2].axis('off')

Example #2

File: plot_localization_tutorial.py Project: rjw57/sklearn-theano

axarr[0, 2].imshow(X)
axarr[0, 2].axis('off')
clf = OverfeatTransformer(force_reshape=False)
X_tf = clf.transform(X[None].astype('float32'))
x_points = np.linspace(0, X.shape[1] - 231, X_tf[0].shape[3])
y_points = np.linspace(0, X.shape[0] - 231, X_tf[0].shape[2])
xx, yy = np.meshgrid(x_points, y_points)
for x, y in zip(xx.flat, yy.flat):
    axarr[0, 2].add_patch(Rectangle((x, y), 231, 231, fc='yellow', ec='black',
                          alpha=.4))

# Get all points with sloth in the top 5 labels
sloth_label = [label for label in get_all_overfeat_labels()
               if 'three-toed sloth' in label][0]
clf = OverfeatLocalizer(match_strings=[sloth_label])
sloth_points = clf.predict(X.astype('float32'))[0]
axarr[1, 0].imshow(X)
axarr[1, 0].axis('off')
axarr[1, 0].autoscale(enable=False)
axarr[1, 0].scatter(sloth_points[:, 0], sloth_points[:, 1], color='orange',
                    s=50)

# Final localization box
sloth_box = convert_points_to_box(sloth_points, 'orange', .6)
axarr[1, 1].imshow(X)
axarr[1, 1].autoscale(enable=False)
axarr[1, 1].add_patch(sloth_box)
axarr[1, 1].axis('off')

# Remove the unused box
axarr[1, 2].axis('off')

Example #3

File: plot_localization_tutorial.py Project: wanjinchang/sklearn-theano

# Show all the boxes being processed
axarr[0, 2].imshow(X)
axarr[0, 2].axis('off')
clf = OverfeatTransformer(force_reshape=False)
X_tf = clf.transform(X)
x_points = np.linspace(0, X.shape[1] - 231, X_tf[0].shape[3])
y_points = np.linspace(0, X.shape[0] - 231, X_tf[0].shape[2])
xx, yy = np.meshgrid(x_points, y_points)
for x, y in zip(xx.flat, yy.flat):
    axarr[0, 2].add_patch(
        Rectangle((x, y), 231, 231, fc='yellow', ec='black', alpha=.4))

# Get all points with sloth in the top 5 labels
sloth_label = "three-toed sloth, ai, Bradypus tridactylus"
clf = OverfeatLocalizer(match_strings=[sloth_label])
sloth_points = clf.predict(X)[0]
axarr[1, 0].imshow(X)
axarr[1, 0].axis('off')
axarr[1, 0].autoscale(enable=False)
axarr[1, 0].scatter(sloth_points[:, 0],
                    sloth_points[:, 1],
                    color='orange',
                    s=50)

# Final localization box
sloth_box = convert_points_to_box(sloth_points, 'orange', .6)
axarr[1, 1].imshow(X)
axarr[1, 1].autoscale(enable=False)
axarr[1, 1].add_patch(sloth_box)
axarr[1, 1].axis('off')

Example #4

File: plot_localization_tutorial.py Project: kastnerkyle/sklearn-theano.github.io

# Show all the boxes being processed
axarr[0, 2].imshow(X)
axarr[0, 2].axis("off")
clf = OverfeatTransformer(force_reshape=False)
X_tf = clf.transform(X[None].astype("float32"))
x_points = np.linspace(0, X.shape[1] - 231, X_tf[0].shape[3])
y_points = np.linspace(0, X.shape[0] - 231, X_tf[0].shape[2])
xx, yy = np.meshgrid(x_points, y_points)
for x, y in zip(xx.flat, yy.flat):
    axarr[0, 2].add_patch(Rectangle((x, y), 231, 231, fc="yellow", ec="black", alpha=0.4))

# Get all points with sloth in the top 5 labels
sloth_label = "three-toed sloth, ai, Bradypus tridactylus"
clf = OverfeatLocalizer(match_strings=[sloth_label])
sloth_points = clf.predict(X.astype("float32"))[0]
axarr[1, 0].imshow(X)
axarr[1, 0].axis("off")
axarr[1, 0].autoscale(enable=False)
axarr[1, 0].scatter(sloth_points[:, 0], sloth_points[:, 1], color="orange", s=50)

# Final localization box
sloth_box = convert_points_to_box(sloth_points, "orange", 0.6)
axarr[1, 1].imshow(X)
axarr[1, 1].autoscale(enable=False)
axarr[1, 1].add_patch(sloth_box)
axarr[1, 1].axis("off")

# Remove the unused box
axarr[1, 2].axis("off")