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Mapping animal exhibits using OpenDroneMap: Part II

Conservation and Research In a previous post, we discussed what does a Zoo Conservation and Research program, like what we are privileged to have at Cleveland Metroparks Zoo do. And what does a program like this do beyond in situ conservation that I’ve blogged about before. Much of the other work done in these programs focuses on research to improve animal care. No matter where … Continue reading Mapping animal exhibits using OpenDroneMap: Part II

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Mapping animal exhibits using OpenDroneMap: orangutan space estimation for the win.

Conservation and Research A little while back, Charles Ritzler, a PhD student with Case Western Reserve University and employee of Cleveland Metroparks Zoo reached out to me. Charles works with Dr. Kristen Lukas, our Director of Conservation and Research, and as such, his work focuses on improving (quoting Dr. Lukas page) “scientific animal management” and “research on the behavior, health, and welfare” of vertebrate species … Continue reading Mapping animal exhibits using OpenDroneMap: orangutan space estimation for the win.

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Old flight meet new flight: Using digital surface models for safer drone flights

Much like the early days of GPS/GNSS, the longer we have drones in the air, the more capacity we build and layer upon previous work. To that end, a colleague of mine has a request to gather video and stills over an area slated for possible installation of a zip line. The request includes flying the path of future zipline. I had concerns whether we … Continue reading Old flight meet new flight: Using digital surface models for safer drone flights

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🌿GRASS is everything❤️‍🔥 (or using GRASS GIS to build elevation models in cities)

In the early days of OpenDroneMap, Dakota Benjamin and I discussed the possibility of integrating GRASS into OpenDroneMap to unlock more approaches for processing and post-processing data. We didn’t pull the trigger at that time, in part due to concerns about expanding the universe of dependencies, but later Piero Toffanin added GRASS to WebODM, and we haven’t looked back. Other libraries and tools at the … Continue reading 🌿GRASS is everything❤️‍🔥 (or using GRASS GIS to build elevation models in cities)

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A new era of open source funding? How we raised $5,099 for core work. — OpenDroneMap

As part of our mission to bring awesome drone software, we focus intensively on sustainability (a.k.a. how to pay for development, bug fixes, new features, hosting, etc. for the benefit of all). Open-source is a tricky type of software to fund. I will not cover the details, as other people have already done a great… A new era of open source funding? How we raised $5,099 … Continue reading A new era of open source funding? How we raised $5,099 for core work. — OpenDroneMap

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Coffee, espresso

🛠➕💘➕🤼🌐=😲☕

Yochai Benkler’s conceptualization of commons-based peer production informs us that affordable tools + love of a topic + people connected across the world creates unusual and interesting innovations. Affordable espresso solutions + the internet (and love of espresso) means that we can expect to see some wonderful innovations in the espresso world, not just in our wonderful cafes, but also in our homes. A cottage … Continue reading 🛠➕💘➕🤼🌐=😲☕

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Screen shot of gauge from multiple perspectives and multiple lighting conditions
3D, AI, blender, Machine Learning

Bean 3 — Gauging the best way to combine Deep Learning and Coffee

In have two previous posts, I sought to combine coffee and deep learning: this one and the latest. Anyone who has been following my blog for a while knows I start with a beginners mind. Lol. In other words, I get almost everything wrong for a while until I sort it out. I appreciate that folx are willing to read along and humor me. My … Continue reading Bean 3 — Gauging the best way to combine Deep Learning and Coffee

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AI, Coffee, Deep Learning

Gauging the best way to combine Deep Learning and Coffee — Bean 2

In a previous post on combining coffee and AI, a combo which makes me think of the kind of marketing genius that was Dinosaur Train (Dinosaurs!: But with trains!::Artificial Intelligence!:But with coffee!), we explored the application of deep learning models to coffee extraction. The underlying question, can we easily and quickly train an deep learning model to read a analog gauge so we can digitize … Continue reading Gauging the best way to combine Deep Learning and Coffee — Bean 2

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