def plot(hist_type):
plt.figure(figsize=(24, 16))
i = 0
for num_bins in [5, 10, 30, 50]:
i += 1
print("Computing %s with %d bins..." % (hist_type, num_bins))
plt.subplot(2, 2, i)
plt.subplots_adjust(hspace=0.5)
plt.title(str(num_bins) + " bins", {'fontsize': 24})
rpc_module.compare_dist_rpc(model_images, query_images,
['chi2', 'intersect', 'l2'], hist_type,
num_bins, ['r', 'g', 'b'])
# plt.savefig("./plots/plt_" + hist_type + ".png")
plt.show()
model_images = fp.readlines()
model_images = [x.strip() for x in model_images]
with open('query.txt') as fp:
query_images = fp.readlines()
query_images = [x.strip() for x in query_images]
num_bins = 20
# %%
plt.figure(1, figsize=(15, 10))
dist_type = ['chi2', 'intersect', 'l2']
hist_model = ['rg', 'rgb', 'dxdy']
Binss = [10, 20, 30, 40]
for bins in Binss:
cols = ['r', 'g', 'b']
for i in range(1, 4):
plt.subplot(1, 3, i)
if i != 2:
rpc_module.compare_dist_rpc(model_images, query_images, dist_type,
hist_model[i - 1], bins, cols)
plt.title(hist_model[i - 1] + ' histograms')
else:
rpc_module.compare_dist_rpc(model_images, query_images, dist_type,
hist_model[i - 1], bins // 2, cols)
plt.title(hist_model[i - 1] + ' histograms')
plt.savefig("hist_bins" + str(bins) + ".png", format='png', dpi=600)
plt.show()
print('number of correct matches: %d (%f)\n' %
(num_correct, 1.0 * num_correct / len(query_images)))
# plot recall_precision curves (Question 4)
with open('model.txt') as fp:
model_images = fp.readlines()
model_images = [x.strip() for x in model_images]
with open('query.txt') as fp:
query_images = fp.readlines()
query_images = [x.strip() for x in query_images]
plt.figure()
rpc_module.compare_dist_rpc(model_images, query_images,
['chi2', 'intersect', 'l2'], 'rg', eval_num_bins,
['r', 'g', 'b'])
plt.title('RG histograms')
plt.show()
plt.figure()
rpc_module.compare_dist_rpc(model_images, query_images,
['chi2', 'intersect', 'l2'], 'rgb',
int(eval_num_bins / 2), ['r', 'g', 'b'])
plt.title('RGB histograms')
plt.show()
plt.figure()
rpc_module.compare_dist_rpc(model_images, query_images,
['chi2', 'intersect', 'l2'], 'dxdy', eval_num_bins,
['r', 'g', 'b'])
with open('model.txt') as fp:
model_images = fp.readlines()
model_images = [x.strip() for x in model_images]
with open('query.txt') as fp:
query_images = fp.readlines()
query_images = [x.strip() for x in query_images]
num_bins = [5,10,20,30,40,50]
for bin_ in num_bins:
plt.figure(8)
rpc_module.compare_dist_rpc(model_images, query_images, ['chi2', 'intersect', 'l2'], 'rg', bin_, ['r', 'g', 'b'])
plt.title('RG histograms '+ str(bin_))
plt.show()
for bin_ in num_bins:
plt.figure(9)
rpc_module.compare_dist_rpc(model_images, query_images, ['chi2', 'intersect', 'l2'], 'rgb', bin_, ['r', 'g', 'b'])
plt.title('RGB histograms '+ str(bin_))
plt.show()
for bin_ in num_bins:
plt.figure(10)
rpc_module.compare_dist_rpc(model_images, query_images, ['chi2', 'intersect', 'l2'], 'dxdy', bin_, ['r', 'g', 'b'])
plt.title('dx/dy histograms '+ str(bin_))
plt.show()
