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https://github.com/bscholer/photogrammetry-abuse
A handful of experiments that mess with images in weird ways to abuse photogrammetry engines.
https://github.com/bscholer/photogrammetry-abuse
drone dronedeploy fun gis mapping
Last synced: about 1 month ago
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A handful of experiments that mess with images in weird ways to abuse photogrammetry engines.
- Host: GitHub
- URL: https://github.com/bscholer/photogrammetry-abuse
- Owner: bscholer
- Created: 2024-08-11T00:19:42.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-10-18T00:45:27.000Z (3 months ago)
- Last Synced: 2024-12-17T01:25:03.738Z (about 1 month ago)
- Topics: drone, dronedeploy, fun, gis, mapping
- Language: Python
- Homepage:
- Size: 155 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Photogrammetry Abuse
This repo contains a framework for messing with images in a variety of ways, in an attempt to make DroneDeploy's photogrammetry engine do weird things.
This doesn't really have much practical purpose, and was really just intended to be a fun experiment.
## Table of Contents
- [Setup](#setup)
- [Usage](#usage)
- [Example Dataset](#example-dataset)
- [Resultant Input Images](#resultant-input-images)
- **[Resultant Maps](#resultant-maps)**
## Setup
1. Clone this repo
2. Create a virtual environment and install the requirements
```bash
python3 -m venv venv
source venv/bin/activate
```
3. Install the requirements
```bash
pip install -r requirements.txt
```
## Usage
For all options, run
```bash
python3 image_processing.py --help
```
### Color Band Removal
This experiment removes the red, green, or blue color band(s) from an image.
For example, to keep the red and green bands and remove the blue band from a set of images (yielding yellow images), run the following command:
```bash
python3 image_processing.py --experiment color-bands \
--input --output \
--bands-to-keep rg
```
### Monochrome
This experiment converts a certain percentage of input images to monochrome (black and white).
For example, to convert 50% of images to monochrome, run the following command:
```bash
python3 image_processing.py --experiment monochrome \
--input --output \
--percentage 50
```
### Flipping and Mirroring
This experiment flips and mirrors certain percentages of input images.
For example, to flip 50% of images upside-down, and mirror 25% of images horizontally, run the following command:
```bash
python3 image_processing.py --experiment inverted \
--input --output \
--flip 50 --mirror 25
```
_Note: This will result in roughly the following distribution (this is somewhat random):_
- 35 % of the images will be flipped upside-down
- 15 % of the images will be mirrored horizontally
- 10 % of the images will be flipped upside-down **and** mirrored horizontally
- 40 % of the images will be left as is
### Random Noise
This experiment adds random noise to images. The percentage of noise is controlled by the `--noise-level` parameter, which is an integer between 0 and 100.
For example, to add 25% noise to images, run the following command:
```bash
python3 image_processing.py --experiment noise \
--input --output \
--noise-level 25
```
### Perspective Warp
This experiment warps the perspective of a certain percentage of input images, by randomly selecting 4 points on the image and warping them by a provided `--warp-by` percentage.
For example, to warp 75% of images by 10% (significant), run the following command:
```bash
python3 image_processing.py --experiment perspective \
--input --output \
--percentage 75 --warp-by 10
```
### Tilt
This experiment tilts a certain percentage of input images by a random angle, between a specficied minimum and maximum angle, in degrees.
For example, to tilt 75% of images by a random angle between -10 and 10 degrees, run the following command:
```bash
python3 image_processing.py --experiment tilt \
--input --output \
--percentage 75 --max-tilt 10
```
### Change GPS
This experiment edits or removes GPS data from a certain percentage of input images.
For example, to remove GPS data from 50% of images, run the following command:
```bash
python3 image_processing.py --experiment set-gps \
--input --output \
--percentage 50
```
To set the GPS data of 100% of images to 44.7471° N, 85.54547° W, run the following command:
```bash
python3 image_processing.py --experiment set-gps \
--input --output \
--percentage 100 --lat 44.7471 --lng -85.54547
```
To set the GPS data of 100% of images to 44.7471° N, 85.54547° W, randomly moved within a 50 meter radius, run the following command:
```bash
python3 image_processing.py --experiment set-gps \
--input --output \
--percentage 100 --lat 44.7471 --lng -85.54547 --max-wiggle 50
```
_Note: When a `--lat` and `--lng` are specified, the altitude is passed through with no change. Future work may include the ability to modify the altitude._
### Remove Pose Metadata
This experiment removes the pose metadata from a certain percentage of input images.
Specifically, these fields are removed from the EXIF data:
- Orientation: Horizontal (normal)
- Gimbal Degree
- Gimbal Roll Degree
- Gimbal Yaw Degree
- Gimbal Pitch Degree
- Flight Degree
- Flight Roll Degree
- Flight Yaw Degree
- Flight Pitch Degree
For example, to remove pose data from 50% of images, run the following command:
```bash
python3 image_processing.py --experiment no-pose \
--input --output \
--percentage 50
```
### Random Timestamps
This experiment adds random timestamps to images, between two provided dates.
For example, to add random timestamps between 2024-01-01 and 2024-01-02 to all the images, run the following command:
```bash
python3 image_processing.py --experiment timestamp \
--input --output \
--start-date 2024-01-01 --end-date 2024-01-02
```
### Upload to DroneDeploy
There is support for automatically uploading modified images to DroneDeploy for processing afterwards. To use this, set the `DD_API_KEY` environment variable to your DroneDeploy API key, and run any of the experiments with the --dd-project-id flag set to the ID of the project you want to upload to.
If you don't care about the output images, you can omit the `--output` flag, which will store the images in a temporary directory before uploading.
You can also specify a `--dd-plan-name`. If one is not provided, a sensical name will be generated based on the experiment and parameters.
For example:
```bash
python3 image_processing.py --experiment no-pose \
--dd-project-id \
--input \
--percentage 50
```
### Trying all of them
To try all of the experiments at once, open `test.sh`, and modify the `INPUT_DIR` and `OUTPUT_BASE_DIR` variables to point to the directories with the images you want to process. Then run the script:
```bash
bash test.sh
```
## Example Dataset
If you don't have a drone or test dataset, feel free to use these images of Baywatch Resort in Traverse City, MI, flown manually with a Mavic Air 2. Images are licensed under the CC BY (Attribution) license, play around and have fun! If you do something cool, make a PR!
[323 Images of Baywatch Resort](https://drive.google.com/file/d/1W3Sd5vwX_MD4Z8u-N8RYf0VTdni6c4ld/view?usp=drive_link)
## Resultant Input Images
Here are some samples from the above example dataset, after running them through `test.sh`!
### Original Image
### Color Band Removal - Removing Blue
### Monochrome
### Inverted - Flipped
### Noise - 50%
### Noise - 95%
### Perspective Warp - Warp by 10%
### Tilt - Random between -10° and 10°
### Set GPS, Remove Pose, and Random Timestamps
All of these experiments only affect metadata, so the images look identical to the original.
## Resultant Maps
These are the results of a handful of experiments! Overall, I'm pretty impressed with how well DroneDeploy handled these weird images, and even with some truly bizzare situations, it still managed to stitch them together reasonably well given how screwed up they are.
### Original Map
Overall, I'm super impressed with how well this map turned out. It isn't hugely surprising given how detailed I was when flying it, but impressive nevertheless!
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/6ed2c63865_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723579200&Signature=GEd3PT/18nVo/lJXmYKTElJgUNOn0mmdhz9PTMNklDj1sSbG9CALVzqmMEiZKb4AvqySKTPamj5qzLJQn7hRUgq9qIWHqTUAzRD1te7OElb3wi6JwqRqd0zaloBu/pNe+YU2FCc++0UMkPvyELVqCo4Rr/xKPcbQCVlBs1oIqB421Dh+xB/PfKt35x9kAhqFMAWqPK/Bh2xHwd3V1jG71UercSt41yk/xf2TPzN1iJLUULFE1lGZX6D3qqJI2XlnqM+DpMhP5qANUUb3/+xvNBln21uaHY+cXCm+xmO+4fZmsSgtfs+/fyz3QMMdcFthUvE4ThkDXD6pvH7hRgPRGA%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b8f825c719dc02218e45e1?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2YjhmODM3ZjdlNzBhOWE0NjUxN2YzYyIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.8YC-TtBYbdvsVtZ1nsI_UrFTGSmC0OaMSGaZoEUGZ68Xw3ZD_-tm9OLiGAn2zVpDWHpzFVnh5Mb02MsKJY6RLg)
### Color Band Removal - Removing Blue
I'm pretty surprised this one turned out as well as it did, but it makes sense. It's just yellow after all!
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/1c9d2fe3bc_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723579200&Signature=EDYWUy7xjtpAKZKW6hznembTCliDHD1OeboscpMIrrXJMMUG/gtjmdmWqj51LvdeTfXmL0+2G6sf4ppX8I5Ww7gGQx/sMHDkf2/aunXH8fCUCd3dOiyxPxzJVC4CkKAksfazgGXlrs0FQO09Rmrm1VhGPmIIYK2/m2CYerwgclwnzDTh0QNQ0zNw7rkdOzAXYyTr4BMGSO38z9gqV+5w8dJUntW0PL+FMiolwv95+pWtxe+F1teJwkqydepBy2/EzzjqEdJGUBSokzbjAR86Vn8vwowoEkcepEFdfuix7y92bgAN3OTWEE6J/WfhIrnr0tCaAvno2N+Iz3o5yv6qRw%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b8ef7fc719dc02218e45d5?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2YjhlZjgyYTJhYWMxZGE3ZWI5NGMwYyIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.97dA5bUsaLJind9kO-fFa5faGVR9v6qTBdMcjmqAr63d2JIXwxV8Nw75eQraVd7y1SX9M8BvpjPG0_ousKhiPg)
### Color Band Removal - Removing Blue and Green
Similar story to removing blue, but this one turned out just fine, just very red!
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/a1dec20914_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723579200&Signature=LymhCAG5wPVFu5ggjh2o2sIYZHcFy40l7Q33P4O4TKEWdlLfrL9bZXnCU1G5doPfBrRdmh9KseBQnt64HwVA9hdiCqn5qsUriD0EIA0FoZLAO52aepvKwab043PrF1XdTfBFU/iq7GhZYl03ysbeFgfhfG6R0KrD+vwyDo5POg47dLtcEx8SCaj4f2QNFSrmEFYzfHfOl++lvgQLWKottaKacyI/17p9pzJ/h89IKE3+kklhy/q0k3BY9qUT5Heuk8FuPjDQu1bAPHWQR61i8MIND9U8wBdthiIZ2cvstScFj8urDUEIB1pYEUDYjuouxMxQZgGNVILG23aRPd52SQ%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b8fe23c719dc02218e45e3?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2YjhmZTI1ZTkxNDBjZmI1ZDNmOTkxYiIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.lNfE56qAGqXqmoG05tarj_yaFLBMGpLdxZAAQZF37KWj5-9AKu_49WIkKWC8RoPGvpFgfHfBxgRv6-_iyTgvtQ)
### Monochrome - 50% of images
Not all that surprising, but there are gray splotches throughout the map, but it looks like the stitcher had no problem with it!
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/78d2cfde3d_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723579200&Signature=U+RY4dIKKrQR+BKKGzxuNiMK2HiNL1AbB6o2kVVkJVdHl9A9KZIeQhotaV4tTZPgsqCdHYiwoBh/7iQWadWwXLThUXnawbXsgVfqsD4WMPbzOZpLxuBJDpnJiiPXCN5CthXDxWbo6N5cPWEAPVOu+NNVIiruUVAvTYW8ZLpS1uypDYNQrluC5fZs0j0glplb+xIOSI9g90W6zGBKZdss81wHIOg81gNr+08IuYIE2gdoFj72ZJKw/jkcyF71VNO62QvFlHKzVXJ3G1ce0lIzb+Gb+cQ/JzoXs43gs0t5Ht7avMdz0197+9Cf0+EgsabQUJbQkpV9AUHwAtSl/mNCjA%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b8f6cbc719dc02218e45df?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2YjhmNmNmZGMwOTcwNjQxZDU2NDNiMSIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.D_8C_piQ_jYxBbFqVbrilynquNQPM32KhylCDcZMCZh3WQJsnWA5zQSBIPeMsmbUkN3YGvO5tTDk493VbkKmpw)
### Inverted - 29% Flipped, 24% Mirrored, 21% Flipped and Mirrored
This one is pretty hilarious! I really had no idea what it would do going into this, but the result isn't surprising. Although, the angle of the upside-down model is unexpected.
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/19f351806c_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723579200&Signature=wXQvTRCj0NMJf6NLWIeCoSORfRCof2B98blKURm8x80XWTTrMTil+REFb9milENsbqXm/FPI9lE/H52oVnA74K4soNn9aJ+8G21VyKWRAeEfjQzMobi/g5Y+bxRr7V+/5f9Q2rIqMX4QH6z+2vlE3plCdkzQVil1NcGMRrSRLLxDtLbMvkTnlwmXzMVr6pBdA14nUw7u2/2kHbh/WcdSocav0kmWn/5oNk1XCUX6ESyvwXa97hnbfOLGPgqju/IFMyLkbNCOnuXTcoQ7o5nC1ONWFFbEtC0dud6MPAl9KX0Z/FJMHNpuZX3qdI37//vz/+Er58VNn2PQyxw2qyHbNw%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b8f075c719dc02218e45d7?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2YjhmMDc5OWViOWM2MjI4Nzc4NGQ1OCIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.ds5DA7b5bIgvLxMwl8wDd9qMLfqiOpChQ7xu615jd4MT0MiSOwtQ6JvtHsRA7SrGnt9saizo2TNMRkP4XHC98w)
### Noise - 25%
Besides being a bit lighter looking, this one turned out just fine, much like the original.
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/aae9b27395_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723579200&Signature=cUtEQoGPzv6qBnzEx8FDfLilkt5itbwpPGqeQWjlIWo/xL/NH/yzjrchsmp5oYsM29IIcP8k6j2Po+EZTb7LocC9cxf/cpHqOzJo0QmVfTafj5/DondI0Ur0T4QhbSaL7bN3ThQA9kU3vYNLnjbV73BHuVGsSdlGNVuSAKmiWlzafGAYFHhu4QLKQtwz+EDMSBdPcuAKUZXghOgbp5FuCzixt97MiG6DK3BjkFCUa9x1/rpZsG+B52oC0Es7i2qfWzxGoW4GmQAMkwl9WN/z7LEJtPCaXwwHb9n+ga+SvI0mkM4F2bTWkQ3FO5zjPW0pzOCW9P/59Qywunq3wDtK8g%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b8f368c719dc02218e45dd?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2YjhmMzZlZjg2ZDU1MDljYTE4ZDZmMyIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.mPvyRcUm8JfRKxYktV6aKrpmrZlpWC0Z8uWJxf0_LK_fUKTLoR2uEAiZXkzbUJ89gN_dtWGNB3BsLxxTARFqsA)
### Noise - 75%
While not _bad_, there is a noticeable degredadation in quality here, as we see this large hole on the side of the building, and an overall decrease in quality from [Noise - 25%](#noise---25), and certainly from the [Original](#original-map).
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/90a36b2b7d_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723604400&Signature=k/UoUFiUK3FI0jRUAljOftOOEj06Ox7hWzswRPMrZfPKL0+ZBU0p0K5bjZRXQPNyK9q6XY4WtrSIVuMKm3j5ylyOLvjCre/3Qhqt6VMXgiMwRNk9qAI/r58GGXnhoDDmoIGllhbSjlc5XAMPzapVEI4tpFJDR/vDPpIf0BLECfC2uVtaIID1IXQYxuBOwACJ1XKkwt5/Luy2QSSb7L20NDKmYFLdRsRAP8DnKsu+gqIwsw4EiM7OGYK3FjIcpDyfO4qQT+zGclgM01hVTbv2XQqFr7ll6LJf1D34dyK/k1fsla/iseh39gpIcWhoSIZAohaqIv3X2+UmYBLK7j8Nlg%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b90c05d00fbf3cb863f5aa?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2YjkwYzBiZTQ1YjBmZjlhOGY0OGQ4NCIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.7uScjyZaoXNOwdBD6oFMBi3VtoIBnwgka-deDKWsxJOJgVSEmqo3I0pkuOSBrTc2J40P7cBARyeteiXxRT8pwA)
### Perspective Warp - 5% Warp on 50% of Images
It feels like I'm finally getting somewhere with breaking photogrammetry! Although, that said, this is still a pretty decent result for some pretty fouled up images. I'm impressed that it seems to have mostly ignored the black borders around the photos, although you can see some odd coloration on the roof..
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/a7ab1f6fcf_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723644000&Signature=aHCrqK5Nr33OaDlCXLpmLiPuf4SrZpejzXqpHIvo3MkIa51sKlOLm2PIeBAzuTDesz6g7+btdMP6gqSYcWkWkuNl0+UMGyKhQ5qWKNIUWFixp11qnchMKl1P62L1bZJXFA7i4958vG2zrOhcYXP2uKcpOX+sS7ziOj1m24aEtBTOeOIjbN6ResUAJFXtWAP3y1QWypznvv0Oea8dDBhJAswu/sngwQ1YfXMwFJBiHRUlzj6PYYg1SyQ5/M1kpFudyVMbv2QFJmrkf8sEaRNZ4Fk5mKT8GMqs1B4chlBxGqkd+zYi9is6TFBSaYjsd4FIXQCnBhGf0lDtD5nuM1g04g%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b98f0ee42b6a0674e79d03?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2Yjk4ZjExYTJhYWMxZGE3ZWI5NGQ1NSIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.M2lgvzcl9HaEuRdGPrzOC3GXsC8qXOKyNSvEgVf3MyQfwSRWyWh-ChSBQOcU9RT0P-FDKaiF8bGxoLyXDDNhcw)
### Perspective Warp - 10% Warp on 75% of Images
Seems like perspective warp will really do a number on photogrammetry! This map looks pretty terrible compared to the [original](#original-map)!
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/bc8ceec662_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723644000&Signature=BIFUThFGteUs3fiLOWpnlW9+G6YHfcZqa9fyAHaAcmgIbdswrs3vyIqS90aVARzPomFUkda9QAjDytWAoJsGYTMNB50AbW6zSsuM05UbEJVhjowQUABtKaDqTRmk2Qich/W3I7mN+J3s2VpdgoOwyNUhgwMroixWbj47zo5nEwBECZvHJ0xbGRwhQyCdmTqB+Q5K2R3/7NaPVQ58s/Sq33KINnPupVD8eAZOOXgroLCWE1jRHms1bhzK+gdAqSM4ZakRrM5RB3MsJqWIVbh2TJYiLNeqKsqIa5cmKgicp/kql57MA4dDNw2rwglFNpsZra1uPMhQ80DNC6fANy8pZQ%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b99003e42b6a0674e79d05?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2Yjk5MDA2ZjI4M2MwY2U3ZTgzOWQ5MiIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.CF6L0NSrACtC0VKzn7drhm16McSFfscdK5muAuNucVYw1DysAlJTRWbbJu__Dr2iiOOB2gyxMbrRUs705I4Y8A)
### Tilt - Between -10° and 10° - 75% of Images
Interestingly, this model turned out surprisingly good! However, you can really clearly see the black boundaries from the photo painted onto the roof. We see a bit of this on the perspective warp experiments, but we see it in full effect here!
[Processing Report](https://storage.googleapis.com/dronedeploy-assets-prod/3d062ed320_C2FDB7A8DCOPENPIPELINE/report.pdf?GoogleAccessId=web-sa-prod@dronedeploy-public.iam.gserviceaccount.com&Expires=1723644000&Signature=HpwQlpto2KtiDrstXUcHjSdMv+6EIAM5W8Znb0+kMe9vGOJ1hafsXlAiFF+E8Jkp3lQGPe5huvtW4R6YBfh3rmCXRIjIuATjZgtOlGZnZnc24D0fS0W1RAbrQZtlBXiG3ha7rrHIuHs/fmFkTY7f5nNB8nOq54xAWpjTdk+O7A66Rc6DM09UxIz3zGm5br+x6z8FADFJQSwLxmXUcIdHw4vjB6mNk/gmqCX6EOedREBHl/76CkYYItvOtvlvpqNEFwLbKAjKPaFWNgGF+zrFHtrKk0tYn3+2CeHjSGRCxcXOeXkKwADcoBcWmUsbYoHYeuEh1pIuf5HOYg4rV7acqw%3D%3D)
| [View map in DroneDeploy](https://www.dronedeploy.com/app2/sites/66b7f6596bc3a8129fffc9cc/maps/66b99754e42b6a0674e79d07?jwt_token=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJpZCI6IjY2Yjk5NzU1MTdkZDkzMjJhNjQxMzc5NCIsInR5cGUiOiJQdWJsaWNTaGFyZVYyIiwiYWNjZXNzX3R5cGUiOiJwbGFuIn0.PcyOfdQ9Mz5LNx3k-pihNWWk8I-G26Mu9uvoFkF01iW0oo5h8RaLxeJW8AreW8NAWt4HGZurfF86P9z3OR_UBQ)
### Set GPS and Random Timestamps
Unfortunately, DroneDeploy is too smart, and the uploader doesn't accept images weird spread out timestamps, images without GPS metadata, or images that all have the same GPS location :(.