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-rw-r--r--utils/raspberrypi/ctt/ctt_macbeth_locator.py69
1 files changed, 40 insertions, 29 deletions
diff --git a/utils/raspberrypi/ctt/ctt_macbeth_locator.py b/utils/raspberrypi/ctt/ctt_macbeth_locator.py
index 3e95df89..178aeed0 100644
--- a/utils/raspberrypi/ctt/ctt_macbeth_locator.py
+++ b/utils/raspberrypi/ctt/ctt_macbeth_locator.py
@@ -57,6 +57,10 @@ def find_macbeth(Cam, img, mac_config=(0, 0)):
"""
cor, mac, coords, msg = get_macbeth_chart(img, ref_data)
+ # Keep a list that will include this and any brightened up versions of
+ # the image for reuse.
+ all_images = [img]
+
"""
following bits of code tries to fix common problems with simple
techniques.
@@ -71,6 +75,7 @@ def find_macbeth(Cam, img, mac_config=(0, 0)):
if cor < 0.75:
a = 2
img_br = cv2.convertScaleAbs(img, alpha=a, beta=0)
+ all_images.append(img_br)
cor_b, mac_b, coords_b, msg_b = get_macbeth_chart(img_br, ref_data)
if cor_b > cor:
cor, mac, coords, msg = cor_b, mac_b, coords_b, msg_b
@@ -81,6 +86,7 @@ def find_macbeth(Cam, img, mac_config=(0, 0)):
if cor < 0.75:
a = 4
img_br = cv2.convertScaleAbs(img, alpha=a, beta=0)
+ all_images.append(img_br)
cor_b, mac_b, coords_b, msg_b = get_macbeth_chart(img_br, ref_data)
if cor_b > cor:
cor, mac, coords, msg = cor_b, mac_b, coords_b, msg_b
@@ -128,23 +134,26 @@ def find_macbeth(Cam, img, mac_config=(0, 0)):
h_inc = int(h/6)
"""
for each subselection, look for a macbeth chart
+ loop over this and any brightened up images that we made to increase the
+ likelihood of success
"""
- for i in range(3):
- for j in range(3):
- w_s, h_s = i*w_inc, j*h_inc
- img_sel = img[w_s:w_s+w_sel, h_s:h_s+h_sel]
- cor_ij, mac_ij, coords_ij, msg_ij = get_macbeth_chart(img_sel, ref_data)
- """
- if the correlation is better than the best then record the
- scale and current subselection at which macbeth chart was
- found. Also record the coordinates, macbeth chart and message.
- """
- if cor_ij > cor:
- cor = cor_ij
- mac, coords, msg = mac_ij, coords_ij, msg_ij
- ii, jj = i, j
- w_best, h_best = w_inc, h_inc
- d_best = 1
+ for img_br in all_images:
+ for i in range(3):
+ for j in range(3):
+ w_s, h_s = i*w_inc, j*h_inc
+ img_sel = img_br[w_s:w_s+w_sel, h_s:h_s+h_sel]
+ cor_ij, mac_ij, coords_ij, msg_ij = get_macbeth_chart(img_sel, ref_data)
+ """
+ if the correlation is better than the best then record the
+ scale and current subselection at which macbeth chart was
+ found. Also record the coordinates, macbeth chart and message.
+ """
+ if cor_ij > cor:
+ cor = cor_ij
+ mac, coords, msg = mac_ij, coords_ij, msg_ij
+ ii, jj = i, j
+ w_best, h_best = w_inc, h_inc
+ d_best = 1
"""
scale 2
@@ -157,17 +166,19 @@ def find_macbeth(Cam, img, mac_config=(0, 0)):
h_sel = int(h/2)
w_inc = int(w/8)
h_inc = int(h/8)
- for i in range(5):
- for j in range(5):
- w_s, h_s = i*w_inc, j*h_inc
- img_sel = img[w_s:w_s+w_sel, h_s:h_s+h_sel]
- cor_ij, mac_ij, coords_ij, msg_ij = get_macbeth_chart(img_sel, ref_data)
- if cor_ij > cor:
- cor = cor_ij
- mac, coords, msg = mac_ij, coords_ij, msg_ij
- ii, jj = i, j
- w_best, h_best = w_inc, h_inc
- d_best = 2
+ # Again, loop over any brightened up images as well
+ for img_br in all_images:
+ for i in range(5):
+ for j in range(5):
+ w_s, h_s = i*w_inc, j*h_inc
+ img_sel = img_br[w_s:w_s+w_sel, h_s:h_s+h_sel]
+ cor_ij, mac_ij, coords_ij, msg_ij = get_macbeth_chart(img_sel, ref_data)
+ if cor_ij > cor:
+ cor = cor_ij
+ mac, coords, msg = mac_ij, coords_ij, msg_ij
+ ii, jj = i, j
+ w_best, h_best = w_inc, h_inc
+ d_best = 2
"""
The following code checks for macbeth charts at even smaller scales. This
@@ -238,7 +249,7 @@ def find_macbeth(Cam, img, mac_config=(0, 0)):
print error or success message
"""
print(msg)
- Cam.log += '\n' + msg
+ Cam.log += '\n' + str(msg)
if msg == success_msg:
coords_fit = coords
Cam.log += '\nMacbeth chart vertices:\n'
@@ -606,7 +617,7 @@ def get_macbeth_chart(img, ref_data):
'\nNot enough squares found'
'\nPossible problems:\n'
'- Macbeth chart is occluded\n'
- '- Macbeth chart is too dark of bright\n'
+ '- Macbeth chart is too dark or bright\n'
)
ref_cents = np.array(ref_cents)