def auto(f,args):
"""
Input:
f -- PIL Image file
args -- arg parsed arguments
Action:
Based on file type, checks for trailing information in file. Print and save if found.
Returns:
Nothing
"""
try:
if f.format == "JPEG":
jpeg(f,args)
elif f.format == "TIFF":
tiff(f,args)
elif f.format == "PNG":
png(f,args)
elif f.format == "BMP":
bmp(f,args)
elif f.format == "GIF":
gif(f,args)
else:
print("Image Trailing: No support yet for format {0}".format(f.format))
return
except:
print("Image Trailing: Something went wrong... please submit a bug report")
def auto(f, args):
"""
Input:
f -- PIL Image file
args -- arg parsed arguments
Action:
Based on file type, checks for trailing information in file. Print and save if found.
Returns:
Nothing
"""
try:
if f.format == "JPEG":
jpeg(f, args)
elif f.format == "TIFF":
tiff(f, args)
elif f.format == "PNG":
png(f, args)
elif f.format == "BMP":
bmp(f, args)
elif f.format == "GIF":
gif(f, args)
else:
print("Image Trailing: No support yet for format {0}".format(
f.format))
return
except:
print(
"Image Trailing: Something went wrong... please submit a bug report"
)
def hello_world():
term=request.args.get('text')
if term:
imglink=gif(term)
else:
imglink=gif("failure")
response = {
"response_type" : "in_channel",
"attachments" : [
{"fallback": "Image search found "+imglink,
"image_url":imglink }
]
}
if len(imglink) > 5:
return jsonify(**response)
else:
return "No gif found :("
def crescendostats(user,action,parameter):
print "Action! " + action
if action == 'tenants':
return listAllTenants()
elif action == 'help':
return getHelp()
elif action == 'metrics over time':
return gif.gif('funny graph')
elif action == 'tenant count':
return tenantCount()
elif action == 'users':
return listAllUsers()
elif action == 'user count':
return userCount()
elif action == 'people count':
return peopleCount()
elif action == 'total signups':
return gif.gif("not done yet")
elif action == 'onboarded':
return gif.gif("not done yet")
elif action == 'summary':
return summary()
elif action == 'get blacklist':
return getBlackList()
elif action == 'blacklist tenant':
print 'param'
print parameter
if parameter is not None and parameter != "":
blackListTenant(parameter)
return getBlackList()
else:
return "YOU SHALL NOT PASS! (without a tenant id)"
elif action == 'unblacklist tenant':
if parameter is not None and parameter != "":
unBlackListTenant(parameter)
return getBlackList()
else:
return gif.gif("YOU SHALL NOT PASS")
else:
print 'BAD THINGS BILL BAD BAD THINGS'
return gif.gif('you done f****d up')
def gif(f,args):
from gif import gif
# Load up the gif
g = gif(fileName=f.filename)
# Parse it
g.parse()
# Check for excess info
if len(g.gif) > 0:
print("Discovered trailing data: {0}".format(g.gif))
with open(os.path.join(args.outDir,"trailing_data.bin"),"wb") as outFile:
outFile.write(g.gif)
def gif(f, args):
from gif import gif
# Load up the gif
g = gif(fileName=f.filename)
# Parse it
g.parse()
# Check for excess info
if len(g.gif) > 0:
print("Discovered trailing data: {0}".format(g.gif))
with open(os.path.join(args.outDir, "trailing_data.bin"),
"wb") as outFile:
outFile.write(g.gif)
def dfs(self, gr: Graph, v: int):
self.marked[v] = True
for w in gr.adjlist(v):
if not self.rmarked(w):
self.edgeTo[w] = v
self.dfs(gr, w)
def hasPathTo(self, v: int) -> bool:
return self.marked[v]
def pathTo(self, v: int) -> list:
if not self.hasPathTo(v):
return None
path = []
path.append(v)
x = self.edgeTo[v]
while x != v:
x = self.edgeTo[x]
path.append(x)
path.append(self.s)
return path
if __name__ == "__main__":
gr = getGr()
df = DFS(gr, 0)
gif()
pass
def main():
#command line argument
parser = argparse.ArgumentParser()
parser.add_argument("-p",
"--plot",
default="no_img",
help="Either no_img, or plot_img")
args = parser.parse_args()
PLOT = args.plot
# load images, which are stored in a folder named 'rectified' in the same directory as this file
data_dir = os.path.dirname(os.path.abspath(__file__))
ic = io.collection.ImageCollection(data_dir + '/rectified/*.png')
half_idx = len(ic) // 2
#load a few frames for testing
'''
left_ic = ic[0+513:500+513]
right_ic = ic[half_idx+513:half_idx+500+513]
ic = None
'''
left_ic = ic[:half_idx]
right_ic = ic[half_idx:]
# images have shape (480, 640, 3)
csv_file = open("points.csv", mode='w')
csv_features_file = open("features.csv", mode='w')
csv_writer = csv.writer(csv_file,
delimiter=',',
quotechar='"',
quoting=csv.QUOTE_MINIMAL)
csv_feature_writer = csv.writer(csv_features_file,
delimiter=',',
quotechar='"',
quoting=csv.QUOTE_MINIMAL)
# initial camera pose
C = np.diag(np.ones(4))
# store the last valid frames in case of skipping frames
prevl = []
prevr = []
pts = np.array([])
for i in range(len(left_ic) - 1):
print("Iteration ", i, "/", len(left_ic) - 1)
# current frame
imgl1 = left_ic[i]
imgr1 = right_ic[i]
imgl2 = left_ic[i + 1]
imgr2 = right_ic[i + 1]
if PLOT.lower() == 'no_img':
matchesl1, matchesr1, matchesl2, matchesr2 = match_features(
imgl1, imgr1, imgl2, imgr2)
if PLOT.lower() == 'plot_img':
matchesl1, matchesr1, matchesl2, matchesr2 = match_features_plot(
imgl1, imgr1, imgl2, imgr2)
if (matchesl1.shape[0] >= 3):
# get matches
F, inliers_a1, inliers_b1, inliers_a2, inliers_b2, = ransac_F_Matrix(
matchesl1, matchesr1, matchesl2, matchesr2)
std_threshold = 2
# triangulate to find real-world points
coords3d1 = triangulate(inliers_a1, inliers_b1)
coords3d2 = triangulate(inliers_a2, inliers_b2)
if (len(coords3d1) == 0 or len(coords3d2) == 0):
print("skipping frame \n")
continue
z1 = coords3d1[:, 2]
z2 = coords3d2[:, 2]
if (i == 0):
pts = np.append(pts, z1)
pts = np.append(pts, z2)
if (len(pts) > 100):
pts = pts[:100]
mean = np.mean(pts)
std = np.std(pts)
mean1 = np.mean(z1)
mean2 = np.mean(z2)
zstd1 = mean1 / std
zstd2 = mean2 / std
print("std:", zstd1, zstd2)
# both frames k and k+1 invalid, skip
if (zstd1 >= std_threshold and zstd2 >= std_threshold):
print("skipping frame \n")
continue
# frame k invalid, frame k+1 valid
elif (zstd1 >= std_threshold and zstd2 < std_threshold):
# use last valid frame if exists, otherwise skip
if (prevl != [] and prevr != []):
matchesl1, matchesr1, matchesl2, matchesr2 = match_features(
prevl, prevr, imgl2, imgr2)
F, inliers_a1, inliers_b1, inliers_a2, inliers_b2, = ransac_F_Matrix(
matchesl1, matchesr1, matchesl2, matchesr2)
coords3d1 = triangulate(inliers_a1, inliers_b1)
coords3d2 = triangulate(inliers_a2, inliers_b2)
else:
print("skipping frame \n")
continue
# frame k valid, frame k+1 invalid
elif (zstd1 < std_threshold and zstd2 >= std_threshold):
prevl = copy.deepcopy(imgl1)
prevr = copy.deepcopy(imgr1)
print("skipping frame \n")
continue
# both frames valid
else:
prevl = []
prevr = []
inliers = coords3d1.shape[0]
coords_abs = C.T @ np.append(
coords3d1, np.ones((inliers, 1)), axis=1).T
csv_feature_writer.writerows(coords_abs[0:3, :].T)
C_new = update_camera_pose(coords3d1, coords3d2, C)
pose_distance = np.linalg.norm(C_new[0:3, 3] - C[0:3, 3])
rejection_threshold = 0.5 #meters
print("Pose", C[0:3, 3])
print("Pose Distance", pose_distance)
if (pose_distance < rejection_threshold):
C = C_new
else:
print("pose rejected")
plot_C[i] = C[0:3, 3].T
csv_writer.writerow(plot_C[i])
print("")
gif(plot_C)
