Example dataset link broken #4

islandmonkey · 2018-10-02T06:52:46Z

unfortunately your example dataset link is broken. Is there any chance you could upload it again?

Cheers

cmbasnett · 2019-07-04T18:42:06Z

I have made a quick-and-dirty script that can generate an example data set from a set of DJI drone images (it extracts the EXIF/XMP data to get the XYZYPR values needed).

import os
from bs4 import BeautifulSoup
from PIL import Image, ExifTags
from pymap3d import ecef2enu, geodetic2ecef
import numpy as np


def dms_to_decimal(d, m, s):
    return d + (m / 60.0) + (s / 3600.0)


def get_gps_coords(im):
    """
    Gets latitude and longitude values from image EXIF data.
    :param im:
    :return:
    """
    exif = im.getexif()
    exif_data = dict()
    for tag, value in exif.items():
        decoded_tag = ExifTags.TAGS.get(tag, tag)
        exif_data[decoded_tag] = value
    gps_info = exif_data['GPSInfo']
    lat_dms = map(lambda x: x[0] / float(x[1]), gps_info[2])
    lat = dms_to_decimal(*lat_dms)
    if gps_info[1] == 'S':
        lat *= -1
    lng_dms = map(lambda x: x[0] / float(x[1]), gps_info[4])
    lng = dms_to_decimal(*lng_dms)
    if gps_info[3] == 'W':
        lng *= -1
    return lat, lng


def get_data(path):
    lat0 = None
    lon0 = None
    h0 = 0
    for root, dirs, files in os.walk(path):
        for filename in sorted(filter(lambda x: os.path.splitext(x)[1].lower() == '.jpg', files)):
            filepath = os.path.join(root, filename)
            with Image.open(filepath) as im:
                for segment, content in im.applist:
                    marker, body = content.split('\x00', 1)
                    if segment == 'APP1' and marker == 'http://ns.adobe.com/xap/1.0/':
                        soup = BeautifulSoup(body, features='html.parser')
                        description = soup.find('x:xmpmeta').find('rdf:rdf').find('rdf:description')
                        pitch = float(description['drone-dji:gimbalpitchdegree']) + 90
                        yaw = float(description['drone-dji:gimbalyawdegree'])
                        roll = float(description['drone-dji:gimbalrolldegree'])
                        alt = float(description['drone-dji:relativealtitude'])
                        lat, lon = get_gps_coords(im)
                        if lat0 is None:
                            lat0 = lat
                            lon0 = lon
                        x, y, z = geodetic2ecef(lat, lon, alt)
                        x, y, z = ecef2enu(x, y, z, lat0, lon0, h0)
                        yield filename, '{:f}'.format(x), '{:f}'.format(y), '{:f}'.format(z), yaw, pitch, roll


def main():
    data = [d for d in get_data('datasets/images')]
    data = sorted(data, key=lambda x: x[0])
    x = np.array(map(lambda d: d[1], data))
    y = np.array(map(lambda d: d[2], data))
    with open('datasets/imageData.txt', 'w+') as f:
        for datum in data:
            f.write(','.join([str(d) for d in datum]) + '\n')


if __name__ == '__main__':
    main()

To get the XYZ values expected by the dataset, the script uses GPS coordinates, converts them from WGS84->ECEF->ENU, with the "origin" of the ENU space being the first image.

If you put images in the datasets/images folder and run this script, you'll get a file called imageData.txt written out in a CSV format like this:

DJI_0023.JPG,0.000000,-0.000000,58.600000,56.2,0.0,0.0
DJI_0024.JPG,6.390588,4.473257,58.599995,56.1,0.0,0.0
DJI_0025.JPG,23.154435,15.434010,58.599939,55.5,0.0,0.0
DJI_0026.JPG,26.520979,17.642848,58.599921,55.7,0.1,0.0

An interesting note, the pitch value treats nadir (straight-down) as 0 degrees pitch, not -90.

Hope this helps some folks getting this working, here's some preliminary results from a few sets of photos:

OpenCV4

I also had to do a few tweaks to get the script working with OpenCV4:

`cv.SURF` is deprecated

The call to cv.SURF(500)was deprecated, and is apparently a patented algorithm that they can't include anymore in modern versions of OpenCV. I simply changed it to use ORB: cv2.ORB_create().

`estimateRigidTransform` is deprecated

The new docs lay out that there are two new functions that do the same thing. In this case, we want to replace the call with A, _ = cv2.estimateAffinePartial2D(src_pts, dst_pts).

alexhagiopol · 2019-07-04T21:12:58Z

Hi @cmbasnett and @island-monkey . I apologize for neglecting this issue for so long. For some reason, I never got an email notification about problem this until Colin posted his message above.

It's true that the Dropbox account where I stored my example data 4 years ago no longer exists. I will try to locate the data, but it's possible it could be lost forever 😔.

Colin's code looks very useful though I have not had the chance to review in detail, and - without the data - I would not be able to test the results myself. I will post here if I am able to come up with a solution.

selva221724 · 2019-11-15T10:31:04Z

I have made a quick-and-dirty script that can generate an example data set from a set of DJI drone images (it extracts the EXIF/XMP data to get the XYZYPR values needed).

import os
from bs4 import BeautifulSoup
from PIL import Image, ExifTags
from pymap3d import ecef2enu, geodetic2ecef
import numpy as np


def dms_to_decimal(d, m, s):
    return d + (m / 60.0) + (s / 3600.0)


def get_gps_coords(im):
    """
    Gets latitude and longitude values from image EXIF data.
    :param im:
    :return:
    """
    exif = im.getexif()
    exif_data = dict()
    for tag, value in exif.items():
        decoded_tag = ExifTags.TAGS.get(tag, tag)
        exif_data[decoded_tag] = value
    gps_info = exif_data['GPSInfo']
    lat_dms = map(lambda x: x[0] / float(x[1]), gps_info[2])
    lat = dms_to_decimal(*lat_dms)
    if gps_info[1] == 'S':
        lat *= -1
    lng_dms = map(lambda x: x[0] / float(x[1]), gps_info[4])
    lng = dms_to_decimal(*lng_dms)
    if gps_info[3] == 'W':
        lng *= -1
    return lat, lng


def get_data(path):
    lat0 = None
    lon0 = None
    h0 = 0
    for root, dirs, files in os.walk(path):
        for filename in sorted(filter(lambda x: os.path.splitext(x)[1].lower() == '.jpg', files)):
            filepath = os.path.join(root, filename)
            with Image.open(filepath) as im:
                for segment, content in im.applist:
                    marker, body = content.split('\x00', 1)
                    if segment == 'APP1' and marker == 'http://ns.adobe.com/xap/1.0/':
                        soup = BeautifulSoup(body, features='html.parser')
                        description = soup.find('x:xmpmeta').find('rdf:rdf').find('rdf:description')
                        pitch = float(description['drone-dji:gimbalpitchdegree']) + 90
                        yaw = float(description['drone-dji:gimbalyawdegree'])
                        roll = float(description['drone-dji:gimbalrolldegree'])
                        alt = float(description['drone-dji:relativealtitude'])
                        lat, lon = get_gps_coords(im)
                        if lat0 is None:
                            lat0 = lat
                            lon0 = lon
                        x, y, z = geodetic2ecef(lat, lon, alt)
                        x, y, z = ecef2enu(x, y, z, lat0, lon0, h0)
                        yield filename, '{:f}'.format(x), '{:f}'.format(y), '{:f}'.format(z), yaw, pitch, roll


def main():
    data = [d for d in get_data('datasets/images')]
    data = sorted(data, key=lambda x: x[0])
    x = np.array(map(lambda d: d[1], data))
    y = np.array(map(lambda d: d[2], data))
    with open('datasets/imageData.txt', 'w+') as f:
        for datum in data:
            f.write(','.join([str(d) for d in datum]) + '\n')


if __name__ == '__main__':
    main()

To get the XYZ values expected by the dataset, the script uses GPS coordinates, converts them from WGS84->ECEF->ENU, with the "origin" of the ENU space being the first image.

If you put images in the datasets/images folder and run this script, you'll get a file called imageData.txt written out in a CSV format like this:

DJI_0023.JPG,0.000000,-0.000000,58.600000,56.2,0.0,0.0
DJI_0024.JPG,6.390588,4.473257,58.599995,56.1,0.0,0.0
DJI_0025.JPG,23.154435,15.434010,58.599939,55.5,0.0,0.0
DJI_0026.JPG,26.520979,17.642848,58.599921,55.7,0.1,0.0

An interesting note, the pitch value treats nadir (straight-down) as 0 degrees pitch, not -90.

Hope this helps some folks getting this working, here's some preliminary results from a few sets of photos:

OpenCV4

I also had to do a few tweaks to get the script working with OpenCV4:

`cv.SURF` is deprecated

The call to cv.SURF(500)was deprecated, and is apparently a patented algorithm that they can't include anymore in modern versions of OpenCV. I simply changed it to use ORB: cv2.ORB_create().

`estimateRigidTransform` is deprecated

The new docs lay out that there are two new functions that do the same thing. In this case, we want to replace the call with A, _ = cv2.estimateAffinePartial2D(src_pts, dst_pts).

HI mate, could you please share your Combiner.py script here... i am not able to come to a solution here, thanks

cmbasnett · 2019-11-15T19:27:27Z

@selva221724 I don't have the script on my machine anymore. The Combiner.py script I used is the same as the one that's in the repository except with the changes I laid out at the bottom of my post.

Sidx369 · 2021-01-28T03:44:26Z

I have made a quick-and-dirty script that can generate an example data set from a set of DJI drone images (it extracts the EXIF/XMP data to get the XYZYPR values needed).

import os
from bs4 import BeautifulSoup
from PIL import Image, ExifTags
from pymap3d import ecef2enu, geodetic2ecef
import numpy as np


def dms_to_decimal(d, m, s):
    return d + (m / 60.0) + (s / 3600.0)


def get_gps_coords(im):
    """
    Gets latitude and longitude values from image EXIF data.
    :param im:
    :return:
    """
    exif = im.getexif()
    exif_data = dict()
    for tag, value in exif.items():
        decoded_tag = ExifTags.TAGS.get(tag, tag)
        exif_data[decoded_tag] = value
    gps_info = exif_data['GPSInfo']
    lat_dms = map(lambda x: x[0] / float(x[1]), gps_info[2])
    lat = dms_to_decimal(*lat_dms)
    if gps_info[1] == 'S':
        lat *= -1
    lng_dms = map(lambda x: x[0] / float(x[1]), gps_info[4])
    lng = dms_to_decimal(*lng_dms)
    if gps_info[3] == 'W':
        lng *= -1
    return lat, lng


def get_data(path):
    lat0 = None
    lon0 = None
    h0 = 0
    for root, dirs, files in os.walk(path):
        for filename in sorted(filter(lambda x: os.path.splitext(x)[1].lower() == '.jpg', files)):
            filepath = os.path.join(root, filename)
            with Image.open(filepath) as im:
                for segment, content in im.applist:
                    marker, body = content.split('\x00', 1)
                    if segment == 'APP1' and marker == 'http://ns.adobe.com/xap/1.0/':
                        soup = BeautifulSoup(body, features='html.parser')
                        description = soup.find('x:xmpmeta').find('rdf:rdf').find('rdf:description')
                        pitch = float(description['drone-dji:gimbalpitchdegree']) + 90
                        yaw = float(description['drone-dji:gimbalyawdegree'])
                        roll = float(description['drone-dji:gimbalrolldegree'])
                        alt = float(description['drone-dji:relativealtitude'])
                        lat, lon = get_gps_coords(im)
                        if lat0 is None:
                            lat0 = lat
                            lon0 = lon
                        x, y, z = geodetic2ecef(lat, lon, alt)
                        x, y, z = ecef2enu(x, y, z, lat0, lon0, h0)
                        yield filename, '{:f}'.format(x), '{:f}'.format(y), '{:f}'.format(z), yaw, pitch, roll


def main():
    data = [d for d in get_data('datasets/images')]
    data = sorted(data, key=lambda x: x[0])
    x = np.array(map(lambda d: d[1], data))
    y = np.array(map(lambda d: d[2], data))
    with open('datasets/imageData.txt', 'w+') as f:
        for datum in data:
            f.write(','.join([str(d) for d in datum]) + '\n')


if __name__ == '__main__':
    main()

To get the XYZ values expected by the dataset, the script uses GPS coordinates, converts them from WGS84->ECEF->ENU, with the "origin" of the ENU space being the first image.

If you put images in the datasets/images folder and run this script, you'll get a file called imageData.txt written out in a CSV format like this:

DJI_0023.JPG,0.000000,-0.000000,58.600000,56.2,0.0,0.0
DJI_0024.JPG,6.390588,4.473257,58.599995,56.1,0.0,0.0
DJI_0025.JPG,23.154435,15.434010,58.599939,55.5,0.0,0.0
DJI_0026.JPG,26.520979,17.642848,58.599921,55.7,0.1,0.0

An interesting note, the pitch value treats nadir (straight-down) as 0 degrees pitch, not -90.

Hope this helps some folks getting this working, here's some preliminary results from a few sets of photos:

OpenCV4

I also had to do a few tweaks to get the script working with OpenCV4:

`cv.SURF` is deprecated

The call to cv.SURF(500)was deprecated, and is apparently a patented algorithm that they can't include anymore in modern versions of OpenCV. I simply changed it to use ORB: cv2.ORB_create().

`estimateRigidTransform` is deprecated

The new docs lay out that there are two new functions that do the same thing. In this case, we want to replace the call with A, _ = cv2.estimateAffinePartial2D(src_pts, dst_pts).

@cmbasnett Can you explain what these numbers separated by comma eg. DJI_0026.JPG,26.520979,17.642848,58.599921,55.7,0.1,0.0 means?

islandmonkey · 2021-01-30T10:09:39Z

@Sidx369
from the code:
'{:f}'.format(x), '{:f}'.format(y), '{:f}'.format(z), yaw, pitch, roll
latitude, longitude, altitude, yaw, pitch, roll

where, in the case of the DJI Phantom, yaw, pitch and roll are the values of the gimbal.
If you don't have a gimbal (i.e. your camera is fixed to the drone frame) just use the yaw, pitch, roll of the drone.

Sidx369 · 2021-01-31T06:08:35Z

Thanks @islandmonkey,
I have an error on running the above script, can anyone tell me how to correct it?
File "C:\Users\Downloads\Aerial repo\orthomosaic\generate_dataset.py", line 44, in get_data marker, body = content.split('\x00', 1) TypeError: a bytes-like object is required, not 'str'

atharva-ak · 2021-02-09T11:34:08Z

@Sidx369 use
marker, body = content.split(b'\x00',1)
for the error, b'\x00' this refers '\x00' as bytes-like object.

AshutoshStark · 2023-09-03T09:51:51Z

the is making the file but it's printing anything can anyone help

code:

import os
from bs4 import BeautifulSoup
from PIL import Image, ExifTags
from pymap3d import ecef2enu, geodetic2ecef
import numpy as np

def dms_to_decimal(d, m, s):
return d + (m / 60.0) + (s / 3600.0)

def get_gps_coords(im):
"""
Gets latitude and longitude values from image EXIF data.
:param im:
:return:
"""
exif = im.getexif()
exif_data = dict()
for tag, value in exif.items():
decoded_tag = ExifTags.TAGS.get(tag, tag)
exif_data[decoded_tag] = value
gps_info = exif_data['GPSInfo']
lat_dms = map(lambda x: x[0] / float(x[1]), gps_info[2])
lat = dms_to_decimal(*lat_dms)
if gps_info[1] == 'S':
lat *= -1
lng_dms = map(lambda x: x[0] / float(x[1]), gps_info[4])
lng = dms_to_decimal(*lng_dms)
if gps_info[3] == 'W':
lng *= -1
return lat, lng

def get_data(path):
lat0 = None
lon0 = None
h0 = 0
for root, dirs, files in os.walk(path):
for filename in sorted(filter(lambda x: os.path.splitext(x)[1].lower() == '.jpg', files)):
filepath = os.path.join(root, filename)
with Image.open(filepath) as im:
for segment, content in im.applist:
marker, body = content.split(b'\x00',1)
if segment == 'APP1' and marker == 'http://ns.adobe.com/xap/1.0/':
soup = BeautifulSoup(body, features='html.parser')
description = soup.find('x:xmpmeta').find('rdf:rdf').find('rdf:description')
pitch = float(description['drone-dji:gimbalpitchdegree']) + 90
yaw = float(description['drone-dji:gimbalyawdegree'])
roll = float(description['drone-dji:gimbalrolldegree'])
alt = float(description['drone-dji:relativealtitude'])
lat, lon = get_gps_coords(im)
if lat0 is None:
lat0 = lat
lon0 = lon
x, y, z = geodetic2ecef(lat, lon, alt)
x, y, z = ecef2enu(x, y, z, lat0, lon0, h0)
yield filename, '{:f}'.format(x), '{:f}'.format(y), '{:f}'.format(z), yaw, pitch, roll

def main():
data = [d for d in get_data("images")]
data = sorted(data, key=lambda x: x[0])
x = np.array(map(lambda d: d[1], data))
y = np.array(map(lambda d: d[2], data))
with open('imageData.txt', 'w+') as f:
for datum in data:
f.write(','.join([str(d) for d in datum]) + '\n')

if name == 'main':
main()
print(main())

Question:.
the is making the file but it's printing anything can anyone help?

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Example dataset link broken #4

Example dataset link broken #4

islandmonkey commented Oct 2, 2018 •

edited

Loading

cmbasnett commented Jul 4, 2019 •

edited

Loading

alexhagiopol commented Jul 4, 2019

selva221724 commented Nov 15, 2019

OpenCV4

`cv.SURF` is deprecated

`estimateRigidTransform` is deprecated

cmbasnett commented Nov 15, 2019

Sidx369 commented Jan 28, 2021 •

edited

Loading

OpenCV4

`cv.SURF` is deprecated

`estimateRigidTransform` is deprecated

islandmonkey commented Jan 30, 2021

Sidx369 commented Jan 31, 2021

atharva-ak commented Feb 9, 2021

AshutoshStark commented Sep 3, 2023

Example dataset link broken #4

Example dataset link broken #4

Comments

islandmonkey commented Oct 2, 2018 • edited Loading

cmbasnett commented Jul 4, 2019 • edited Loading

OpenCV4

cv.SURF is deprecated

estimateRigidTransform is deprecated

alexhagiopol commented Jul 4, 2019

selva221724 commented Nov 15, 2019

OpenCV4

cv.SURF is deprecated

estimateRigidTransform is deprecated

cmbasnett commented Nov 15, 2019

Sidx369 commented Jan 28, 2021 • edited Loading

OpenCV4

cv.SURF is deprecated

estimateRigidTransform is deprecated

islandmonkey commented Jan 30, 2021

Sidx369 commented Jan 31, 2021

atharva-ak commented Feb 9, 2021

AshutoshStark commented Sep 3, 2023

islandmonkey commented Oct 2, 2018 •

edited

Loading

cmbasnett commented Jul 4, 2019 •

edited

Loading

`cv.SURF` is deprecated

`estimateRigidTransform` is deprecated

`cv.SURF` is deprecated

`estimateRigidTransform` is deprecated

Sidx369 commented Jan 28, 2021 •

edited

Loading

`cv.SURF` is deprecated

`estimateRigidTransform` is deprecated