A noteworthy geotagging application is HoudahGeo by Houdah Software. It has an extraordinarily tidy user interface that comfortably leads you through the three main steps of geotagging: picking images, merging geodata and creating output files. But is ist just tidy on the outside? We tested the latest version HoudahGeo 2.2.5, released only yesterday.
HoudahGeo
Test Setup
See my “Test Scenario” post.
Preliminary Steps
HoudahGeo’s preference pane offers some useful options that you may want to activate prior to start working with it. Namely, support for iPhoto and other libraries and very handy presets for manual geotagging.
HoudahGeo directly accesses iPhoto, Aperture and Lightroom libraries. It is the only geotagging application I know that writes back both directly into iPhoto-managed image files and the iPhoto library.
Faster manual geotagging is possible if "automatically proceed to next image" is activated in both "Geocoding" tabs.
Putting HoudahGeo at the beginning of any imaging workflow is a good idea, and is also the procedure recommended by Houdah Software. (This is specifically important if you are using iPhoto!)
Log-Based Workflow
HoudahGeo's user interface is color-coded to distinguish the three main steps of geotagging. The first - red - section offers image importing options.
A typical session with HoudahGeo requires very little help from the manual as the interface is pretty tidy with clear tool tips and contextual hints.
We first walk through our log-based workflow, merging images with a track log. The following end-to-end workflow took less than two minutes: load images, indicate timezone, load track log, check result and save output files.
Step 1: Adding Images (Red Section)
As defined in our test scenario, we load CR2 images from a folder on our harddisk using the “add images from files” button of the red section.
On import, HoudahGeo asks what time zone the camera was set to and whether there was any additional deviation in minutes.
On import, we choose the timezone of the camera’s internal clock when the images were taken. Remember that the timezone indicator for the same location changes when DST rules! With your clock set to the ruling local time, add one hour during summer, e.g. GMT+2 instead of GMT+1, and vice versa. You may also pick your regional timezone indicator from the dropdown, such as “Europe/London”: in this case DST is automatically observed (if the camera was set correctly). If your camera was not set to local time I recommend you run the Automator action described in my timezones post first.
In the second line of HoudahGeo’s dialog, time deviation in minutes may be entered if the camera’s clock is fast or slow. Don’t worry if you are not sure about this: you may always get back to this dialog later in the workflow.
Please keep in mind that this step concerns the camera only, not the track log file! GPS units take their time from satellites – their track logs do not have to be corrected.
Step 2: Merging Geodata (Yellow Section)
In order to merge the files with our locally stored GPX log, we use the “load GPS data from file” icon in the yellow area. HoudahGeo automatically matches images to coordinates if possible.
Step 2 - the yellow section - offers options for geodata merging. Those include track logs, manual tagging via Google Maps or Google Earth and reverse geocoding.
After successfully loading the GPX file, HoudahGeo automatically jumps to the green export section. Even though all images now carry geotags, it is a good idea to check the preview and map windows whether they are correctly matched.
There are generally two possibilities why an image may appear at the wrong location: either the camera’s time zone and deviation were not set correctly and all images are off their original location by some degree. Or an individual image fell victim of a weak satellite reception at the time.
The first problem can be solved by setting the camera’s time and deviation from the “Images >> Camera Setup” menu, i.e. correcting the values entered on import. The second problem can be solved by re-positioning the pin in either of the “Geocoding” dialogs (third and fourth icon in the yellow area). We will explain how to do this in the “Manual Workflow” section below.
If both your clock sync and satellite reception were good but you are still facing issues, you may try the expert option: under the menu "Geocode >> Geocode from Tracks & Waypoints" you can influence the interpolation method used.
Optionally, more location data can be retrieved through the “Reverse Geocoding” dialog. The latest version of HoudahGeo also fetches altitude values.
After adding EXIF geodata, HoudahGeo can populate the IPTC location fields via the reverse geocoding button. Google Maps and GeoNames can alternatively be used as sources. Additionally, altitude values can be retrieved.
Step 3: Creating Output Files (Green Section)
Now, with all geodata retrieved for our image set, HoudahGeo offers various export options: save metadata, export to Google Earth (KMZ) or KML, Flickr or Locr. We follow our test scenario and save the metadata tags (see below for metadata integrity and KML/KMZ export).
In the third step - the green area - HoudahGeo offers the option to write EXIF/XMP/IPTC tags. The dialog offers several options.
A choice of sensible options meets different archiving needs: “always write XMP sidecar” leaves the image files untouched, but adds an XMP file, “create copies” preserves the content of the source directory. If you check “Timestamp”, timezone offset is added to the EXIF data and GPS date/time values are created (recommended if you did not run my timezone script before). If you leave the “artist” option checked, the name of the current MacOS user is entered into the corresponding field.
Manual Workflow
Manual geotagging is your choice if you either do not have a GPS unit or track log, or if coordinates from a log-based workflow were off to some degree due to bad satellite reception.
HoudahGeo offers two possibilities to geotag images manually, either through Google Maps or Google Earth. Both have their specific advantages: while Google Maps is faster at startup and lets you quickly switch between three alternative map views, Google Earth can be used offline in a limited way (location must be in cache beforehand). According to Pierre Bernard from Houdah Software, HoudahGeo is currently tested for future support of other mapping providers.
In the Google Maps dialog, the image's location can be set by dragging and dropping a marker with crosshairs.
The Google Maps dialog is very tidy and shows the familiar toolbars and options. If you enabled “automatically proceed to next image” in the preferences pane, your workload is reduced to a minimalistic two clicks per image. Conveniently, the dialog also includes a bookmarking feature to quickly jump to your favourite locations.
Adding geotags in Google Earth is equally easy: a crosshairs marker makes tagging easy. If the terrain layer is activated, altitude values are automatically inserted.
The fourth button of HoudahGeo’s yellow toolbar section launches Google Earth and a geotagging panel. With preferences set to “automatically proceed to next image” and the terrain layer activated it is marginally more efficient than its sibling, because altitude values are automatically added. In my tests, altitude values were determined more reliably here than through the “Reverse Geocoding” dialog were results seem to be heavily interpolated.
If you use either of both dialogs to correct already tagged images, the map will automatically center to the image’s location. This makes re-tagging really fast. Conveniently, any number of highlighted images from the same spot can be tagged in one go.
Metadata QA
Houdah Software have done their homework thoroughly: when writing metadata, all existing entries stay untouched while new values are entered correctly. This is probably due to the fact that they wisely put Phil Harvey’s ExifTool at the core of their metadata engine (just as they integrated GPSBabel for direct link-up to GPS units).
Comparing the images' metadata before and after they were processed in HoudahGeo reveals the non-destructive character of its geotagging algorithm.
I did a few runs with various file types – geotagged and untagged DNG and CR2 files – and got issues only in a rather improbable constellation where different values were used in CR2 files and the corresponding fields of their XMP sidecars (Lightroom always only uses XMP sidecars for CR2 metadata).
KML/KMZ Support
Creating map-based slideshows or publishing maps with images online is usually done with the help of the Keyhole Markup Language (KML). This is a XML standard, meaning it is represented by a simple text file with instructions and links. The markup language is not complicated, but with a larger number of images and individual formatting ideas it just gets to large to type it out.
HoudahGeo offers support for KML/KMZ output, the latter hidden under the “Export to Google Earth” button. The difference between the two formats is marginal, as KMZ is basically a ZIP archive containing a KML folder structure, i.e. XML file and related images. Both KML and KMZ can be used in Google Earth and online maps.
KMZ files can be opened directly in Google Earth. Using the "Tour" function, the images are displayed as a slideshow within the map.
A sample KMZ file to view in Google Earth can be downloaded from here (ca. 400 KB).
HoudahGeo creates both output types in an acceptable form, but the export options are highly limited. Except for the preview size users cannot influence the layout in which the images are displayed, nor can they choose which metadata shows up.
According to Pierre Bernard, there are plans to provide greater flexibility and formatting options in a future version of HoudahGeo.
Conclusion: Smoothness and Reliability
HoudahGeo gets full score under the scrutiny of our Nine Requirements: showing an amazing swiftness and ease of use it creates standards-compliant geotagged images, offering sensible alternative approaches to meet individual preferences. With the top rating in terms of smoothness and reliability, HoudahGeo is the geotagging reference other applications have to be measured against.
Needless to say that HoudahGeo is well worth the $30 price tag.
Test Results Overview
CR2, DNG, JPG etc.iPhoto (both source files and database), Aperture, LightroomGPX, NMEA; GPS devices via GPSBabelTimezone and clock deviation
Basic administration (add/delete/rename tracks in track library)Automatic, with batch correctionGoogle Maps and Google Earth, including altitude values, fast 2-click taggingMetadata integrity is observed (non-destructive on existing entries), selective output and XMP sidecar optionCreates both formats; only limited control over layout and content, though.See my introductory post for more details on the Nine Requirements.
Documentation
On-board user manual is useful for the most common tasks; some in-depth explanations (metadata etc.).Excellent documentation with extensive FAQ section, video tutorials and screenshots. Forum and e-mail support are actively maintained.Application Details
Related Posts
- All posts in “Geotagging” category
- Geotagging and the Mac (1) – Basics
- Geotagging and the Mac (2) – Test Scenario
- Geotagging and the Mac (3) – iPhoto ’09 “Places”
- Geotagging and the Mac (5) – Google Picasa
Updates
- April 23rd, 2009: updated “Step 1″ section (alternative timezone setting), added rating plate
- May 8th, 2009: added note that Google Earth’s altitude values seem to be more reliable
Tags: Geotagging, Mac, Review, Software
Hi!
Thanks for your overview. Very helpful. Two small questions:
(1) Which tool do you display under the Section “Metadata QA” to show all Metadata?
(2) How do you manage to make Google Maps point to a kmz file? And how do you integrate that into a web page.
Thanks a lot,
frank
Hi Frank,
to compare the two text files I used Apple’s FileMerge which comes bundled with MacOS X. You might need to install the Apple Developer Tools from your MacOS X installation disk first. Another useful diff tool is kdiff3 (http://kdiff3.sourceforge.net/).
The easiest way to make Google Maps point to a KMZ file is to upload it to your server and then simply enter the full URL to this file into Google Maps’ search field. Using the URL query string (e.g. http://maps.google.com/maps?q=http:%2F%2Fstudio.messlinger.com%2Fwp-content%2Ftracks%2F2009%2FHeidelberg%2FHoudahGeo.kml) you can forward it to somebody else via e-mail.
If you want to integrate a KMZ map into your website, you might want to read Google’s API description (http://code.google.com/intl/en-EN/apis/maps/). Remember to get your free Google API key first. A good starting point to understand the concept is Google’s Map Search Wizard (http://www.google.com/uds/solutions/wizards/mapsearch.html).
Klaus
Thanks a lot.
This is a very good review/overview of what’s probably the most popular geotagging application for the Mac. I used it myself for over a year to geotag my photos.
However since a couple of weeks my geotagging workflow became a lot simpler. I’m using my iPhone 3G to track my position during my photoshoots and afterwards the app I use (GeoLogTag) geotags the photos over WiFi. All I need to do, is configure the folder with the photos as a shared folder.
I’m still a big fan of HoudahGeo and I would recommend it to anyone who uses a separate GPS data logging device, but if you have an iPhone I would recommend GeoLogTag.
http://www.galarina.eu/GeoLogTag/Home.html
Thanks for the hint, Herman. Definitely very useful for iPhone users.
However, you would have to rely on iPhone always having perfect satellite/WiFi reception and on a perfect sync with your camera’s clock. In my experience, this remains an issue and therefore requires a second look at the result – which is why HoudahGeo remains very useful even for GeoLogTag users.
Finally, I am notoriously suspicious when it comes to metadata integrity: many applications wreak havoc on existing metadata when inserting geotags. I don’t know how well GeoLogTag performs, but I would definitely recommend testing its results (e.g. by running the “reading all metadata” script from my “ExifTool and the Automator” post).
Klaus
“If you leave the “artist” option checked, the name of the current Mac OS user is entered into the corresponding field.”
Actually not. I discovered it’s the First name + Last name of the “Me” card in Address book, because it has an accent in my first name there, and not in Mac OS user name.
Thanks for pointing this out, Francois.
K.
I tried HoudahGeo for a while but since I’m a Lightroom fanatic I much preferred the simplicity of Jeffrey Friedl’s Geoencoding Plugin for Lightroom.
Screenshot link for plugin… http://regex.info/blog/2008-10-29/979
Thanks for your comment, Tom.
I really like the extensions and tools Jeffrey has developed over the years: his input helped me tailor Lightroom to a perfect fit for my needs in most areas.
However, he admits himself that his GPS plugin is some kind of a workaround as it uses something he calls “shadow data”. So, instead of storing geotags inside the actual files, you will have to export them first to create a durable archive (that is what I call an infringement of the “travelling standards” paradigm). To me, this alone is a no-go, as you never know how long Lightroom is going to be around and whether you will be able to migrate this shadow data to any future imaging application. That would be lot of work down the drain…
Secondly, the plugin only supports logfile-based workflows. With my Garmin handset I often experience quite an offset between the measured and the correct location. If I want to put that right, I need some visual aid like Google Maps to quickly drag a location pin to the right spot.
HoudahGeo is my first choice as it fits nicely into the first step of my Lightroom workflow: I geotag my images before importing them into LR. This is my workflow: copy to harddisk > reduce to keeps > geotag > import into LR > rest of metadata > development > done.
I recommend you have a look at my first geotagging post to get my drift. There is also some information in the second post “Useful Tools for Geotagging” that you might find helpful.
Thanks,
Klaus
EDIT: There was the question about my workflow, why and how I reduce my RAW files to keeps outside Lightroom.
Why: As I geotag before importing into LR, I prefer to have less files to deal with. And I don’t want LR to carry out time-consuming DNG conversion on images I won’t keep.
How: You may of course always use your Mac’s Quicklook function (spacebar) for sorting out your images. But that has the disadvantage that after you delete a file, the marker jumps back up to directory level and you would have to scroll back down to see the next image.
The usual suspect would be Preview: just drag your import folder on the Preview icon to use its browsing function. But I find it a bit slow (maybe that’s because it first reads all files).
For me, the ideal solution is using a stand-alone viewer like Xee or ViewIt. These viewers read images very fast and they allow you to delete files in fullscreen mode while maintaining the position in the file order. ViewIt is very similar to Xee, but it has one great advantage: while Xee only pre-loads one image, ViewIt keeps at least three in its preview memory (forward and back) which makes eliminating much faster.