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app.py
CHANGED
@@ -196,7 +196,6 @@ def generate_matching_superfeatures(im1, im2, Imagenet_model=False, scale_id=6,
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if j == 0: col_ = col.colors[9]
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col_ = 255*np.array(colors.to_rgba(col_))[:3]
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img1rsz[m,n, :] = col_[::-1]
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fin_img.append(img1rsz)
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img2rsz = np.copy(im2_cv)
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print('im2:', im2.size)
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@@ -214,7 +213,6 @@ def generate_matching_superfeatures(im1, im2, Imagenet_model=False, scale_id=6,
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# if j == 0: col_ = col.colors[9]
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col_ = 255*np.array(colors.to_rgba(col_))[:3]
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img2rsz[m,n, :] = col_[::-1]
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fin_img.append(img2rsz)
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fig1 = plt.figure(1)
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plt.imshow(cv2.cvtColor(img1rsz, cv2.COLOR_BGR2RGB))
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@@ -231,29 +229,13 @@ def generate_matching_superfeatures(im1, im2, Imagenet_model=False, scale_id=6,
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ax2.axis('off')
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plt.tight_layout()
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# fig2.canvas.draw()
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# fig = plt.figure()
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# grid = ImageGrid(fig, 111, nrows_ncols=(2, 1), axes_pad=0.1)
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# for ax, img in zip(grid, fin_img):
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# ax.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
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# ax.axis('scaled')
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# ax.axis('off')
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# plt.tight_layout()
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# fig.suptitle("Matching SFs", fontsize=16)
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# fig.canvas.draw()
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# # Now we can save it to a numpy array.
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# data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
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# data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
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f = lambda m,c: plt.plot([],[],marker=m, color=c, ls="none")[0]
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handles = [f("s", col.colors[i]) for i in range(n_sf_ids)]
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fig_leg = plt.figure(3)
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legend = plt.legend(handles, sf_idx_, framealpha=1, frameon=False, facecolor='w',fontsize=15, loc="center")
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# fig_leg = legend.figure
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fig_leg.canvas.draw()
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ax3 = plt.gca()
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# ax2.axis('scaled')
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ax3.axis('off')
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if j == 0: col_ = col.colors[9]
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col_ = 255*np.array(colors.to_rgba(col_))[:3]
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img1rsz[m,n, :] = col_[::-1]
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img2rsz = np.copy(im2_cv)
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print('im2:', im2.size)
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# if j == 0: col_ = col.colors[9]
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col_ = 255*np.array(colors.to_rgba(col_))[:3]
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img2rsz[m,n, :] = col_[::-1]
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fig1 = plt.figure(1)
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plt.imshow(cv2.cvtColor(img1rsz, cv2.COLOR_BGR2RGB))
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ax2.axis('off')
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plt.tight_layout()
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# fig2.canvas.draw()
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f = lambda m,c: plt.plot([],[],marker=m, color=c, ls="none")[0]
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handles = [f("s", col.colors[i]) for i in range(n_sf_ids)]
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fig_leg = plt.figure(3)
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legend = plt.legend(handles, sf_idx_, framealpha=1, frameon=False, facecolor='w',fontsize=15, loc="center")
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# fig_leg = legend.figure
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# fig_leg.canvas.draw()
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ax3 = plt.gca()
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# ax2.axis('scaled')
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ax3.axis('off')
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