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Dataset results
341 results for “RES”
Mechanical alphabet, TM1981 (Low res.)
Christopher Polhem (1661-1751) created the so-called mechanical alphabet in the years just before 1700. The wooden models illustrated the fundamentals of physics and mechanics and were intended to serve as an educational tool in teachings at the Laboratorium mechanicum established in 1697. After his death, the collection continued to serve as a didactic instrument and became part of the Swedish Royal Model Chamber. In 1925, the collection of 31 models was deposited at the newly established National Museum of Science and Technology. [TM1981](https://digitaltmuseum.se/021026544982/mekaniskt-alfabet-modell?aq=text%3A%22polhem%22+owner%3A%22S-TEK%22&i=23"tm1981") (TEKS0021248) Created in RealityCapture by Fredrik Olsson from 363 images in 02h:08m:42s. Please note: No post processing have been done, holes may occur in mesh. Read more about [Polhem]( https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Mechanical alphabet, TM1971 (Low res.)
Christopher Polhem (1661-1751) created the so-called mechanical alphabet in the years just before 1700. The wooden models illustrated the fundamentals of physics and mechanics and were intended to serve as an educational tool in teachings at the Laboratorium mechanicum established in 1697. After his death, the collection continued to serve as a didactic instrument and became part of the Swedish Royal Model Chamber. In 1925, the collection of 31 models was deposited at the newly established National Museum of Science and Technology. [TM1971](https://digitaltmuseum.se/021026493579/mekaniskt-alfabet-modell?aq=owner%3A%22S-TEK%22+text%3A%22polhem%22&i=16"tm1971") (TEKS0021139) Created in RealityCapture by Fredrik Olsson from 62 images in 00h:04m:23s. Please note: No post processing have been done, holes may occur in mesh. Read more about [Polhem](https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Mechanical alphabet, TM1975 (Low res.)
Christopher Polhem (1661-1751) created the so-called mechanical alphabet in the years just before 1700. The wooden models illustrated the fundamentals of physics and mechanics and were intended to serve as an educational tool in teachings at the Laboratorium mechanicum established in 1697. After his death, the collection continued to serve as a didactic instrument and became part of the Swedish Royal Model Chamber. In 1925, the collection of 31 models was deposited at the newly established National Museum of Science and Technology. [TM1975](https://digitaltmuseum.se/021026544940/mekaniskt-alfabet-modell?aq=text%3A%22polhem%22+owner%3A%22S-TEK%22&i=34"tm1975") (TEKS0021182) Created in RealityCapture by Fredrik Olsson from 244 images in 01h:40m:20s. Please note: No post processing have been done, holes may occur in mesh. Read more about [Polhem]( https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Ballet costume, rose leotard HIGH RES.
Teos/Title: Le Spectre de la Rose (Ruusu-unelma)/ Le Spectre de la Rose (The Spirit of the Rose) Tuotanto/Production: Mahdollisesti Kari Karnakosken ja Lucia Nifontovan kiertue 1947/possibly used during a tour in Finland 1947 Koreografia/Choreography: Mihail Fokinin mukaan/according to Michel Fokine Säveltäjä/Composer: Carl Maria von Weber Pukusuunnittelu/Costume design: Kari Karnakoski Tanssija/Dancer: Kari Karnakoski Rooli/Role: Ruusu/ The Rose Ruusu-unelma kertoo tarinan nuoresta tytöstä, joka uneksii tanssivansa eloon heränneen ruusun kanssa. Kari Karnakoski esiintyi Ruusu-unelmassa työskennellessään ensitanssijana Le Ballet Russe de Paris'ssa 1930-luvulla. Hän palasi Ruusun rooliin vuonna 1947 kiertueella, jonka teki yhdessä Lucia Nifontovan kanssa Suomessa, mutta esiintymisiä oli myös Tukholmassa ja Oslossa. Tämä puku on mahdollisesti vuoden 1947 kiertueen puvustusta, jonka Kari itse suunnitteli. Matalaresoluutioversio/Low-Res version: https://skfb.ly/o6HrQ 3D model by Ninma Oy Source: Objaverse 1.0 / Sketchfab
Mechanical alphabet, TM1997 (Low res.)
Christopher Polhem (1661-1751) created the so-called mechanical alphabet in the years just before 1700. The wooden models illustrated the fundamentals of physics and mechanics and were intended to serve as an educational tool in teachings at the Laboratorium mechanicum established in 1697. After his death, the collection continued to serve as a didactic instrument and became part of the Swedish Royal Model Chamber. In 1925, the collection of 31 models was deposited at the newly established National Museum of Science and Technology. [TM1997](https://digitaltmuseum.se/021026545025/mekaniskt-alfabet-modell?i=22&aq=owner%3A%22S-TEK%22+text%3A%22polhem%22"tm1997") (TEKS0021422) Created in RealityCapture by Fredrik Olsson from 317 images in 00h:56m:47s. Please note: No post processing have been done, holes may occur in mesh. Read more about [Polhem]( https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Mechanical alphabet, TM1976 (Low res.)
Christopher Polhem (1661-1751) created the so-called mechanical alphabet in the years just before 1700. The wooden models illustrated the fundamentals of physics and mechanics and were intended to serve as an educational tool in teachings at the Laboratorium mechanicum established in 1697. After his death, the collection continued to serve as a didactic instrument and became part of the Swedish Royal Model Chamber. In 1925, the collection of 31 models was deposited at the newly established National Museum of Science and Technology. [TM1976](https://digitaltmuseum.se/021026351764/mekaniskt-alfabet-modell?aq=owner%3A%22S-TEK%22+text%3A%22polhem%22&i=36"tm1976") (TEKS0021192) Created in RealityCapture by Fredrik Olsson from 124 images in 00h:07m:28s. Please note: No post processing have been done, holes may occur in mesh. Read more about [Polhem](https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Mechanical alphabet, TM1361 (Low res.)
Christopher Polhem (1661-1751) created the so-called mechanical alphabet in the years just before 1700. The wooden models illustrated the fundamentals of physics and mechanics and were intended to serve as an educational tool in teachings at the Laboratorium mechanicum established in 1697. After his death, the collection continued to serve as a didactic instrument and became part of the Swedish Royal Model Chamber. In 1925, the collection of 31 models was deposited at the newly established National Museum of Science and Technology. [TM1361](https://digitaltmuseum.se/021026544835/mekaniskt-alfabet-modell?i=43&aq=owner%3A%22S-TEK%22+text%3A%22polhem%22"tm1361") (TEKS0014716) Created in RealityCapture by Fredrik Olsson from 381 images in 00h:58m:13s. Please note: No post processing have been done, holes may occur in mesh. Read more about [Polhem]( https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Christ Church, Stannington, Doncaster (High res)
Project note: This model was created using high alignment, dense point cloud and 8192 x 2 texturing providing a higher resolution result. Funding for this project has been provided by the Heritage Lottery Fund. Christ Church is a Commissioners' Church or "Million Church" as it was built partly with money provided by the Church Building Act of 1824. It is designated by English Heritage as a Grade II listed building. The construction of Christ Church was completed in 1830. The final cost of the church was £3,000 with part of the funding coming from the second parliamentary grant of the Church Building Act which was approved in 1824. However a substantial donation came from Eliza and Ann Harrison of Weston Hall, daughters of Thomas Harrison an eminent Sheffield sawmaker. Find out more here http://www.christchurchstannington.co.uk/Groups/253362/Our_History.aspx Source: Objaverse 1.0 / Sketchfab
Antinoüs Mondragone (High Res)
**Antinoüs Mondragone** Portrait colossal posthume du favori de l'empereur Hadrien (117 - 138 après J.-C.). Les yeux et un attribut au sommet du crâne (une fleur de lotus ? un uræus ?) étaient rapportés. Le buste s'insérait dans un corps sans doute taillé dans un autre matériau. Au début du XIXe siècle, le buste était exposé à la villa Mondragone que les Borghèse possédaient près de Rome. Vers 130 après J.-C. Italie Marbre H. : 95 cm. Musée du Louvre. Paris (Photoscan / Zbrush) Source: Objaverse 1.0 / Sketchfab
Ancestral Puebloan Clay Bowl High Res
Ancestral Puebloan clay bowl on display at the Hutchings Museum. 173 images, Canon EOS 80D, 35mm, F/16, ISO 100, Agisoft Metashape, Windows 10. Source: Objaverse 1.0 / Sketchfab
Mechanical alphabet, TM1360 (Low res.)
Christopher Polhem (1661-1751) created the so-called mechanical alphabet in the years just before 1700. The wooden models illustrated the fundamentals of physics and mechanics and were intended to serve as an educational tool in teachings at the Laboratorium mechanicum established in 1697. After his death, the collection continued to serve as a didactic instrument and became part of the Swedish Royal Model Chamber. In 1925, the collection of 31 models was deposited at the newly established National Museum of Science and Technology. [TM1360](https://digitaltmuseum.se/021026544809/mekaniskt-alfabet-modell?i=32&aq=owner%3A%22S-TEK%22+text%3A%22polhem%22"tm1360") (TEKS0014705) Created by Fredrik Olsson in RealityCapture from 362 images. Please note: No post processing have been done, holes may occur in mesh. Read more about [Polhem]( https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Ballet costume, rococo style dress HIGH RES.
Teos/Title: Les bons vieux temps Tuotanto/Production: Suomen Punaisen Ristin hyväntekeväisyysnäytäntö Suomalaisessa Oopperassa (nyk. Suomen kansallisooppera ja -baletti) 13.12.1926 / A charity gala of the Finnish Red Cross at the Finnish Opera (now the Finnish National Opera and Ballet) 13 Dec 1926 Koreografi/Choreographer: Edith von Bonsdorff ja/tai / and/or George Gé Säveltäjä/Composer: Wolfgang Amadeus Mozart Tanssija/Dancer: Mary Paischeff Mary Paischeff (1899–1975) oli ensimmäinen Suomalaisen Oopperan balettiin sopimuksen tehnyt tanssija. Hän tanssi Joutsenlammen haastavan Odette/Odile -kaksoispääroolin vuonna 1922 Oopperan baletin avajaisnäytännössä. Paischeff käytti rokokootyylistä pukua ainakin Suomen Punaisen Ristin hyväntekeväisyysnäytännössä Suomalaisessa Oopperassa tanssiessaan yhdessä George Gén kanssa. Matalaresoluutioversio / Low-Res version: https://skfb.ly/o6H8p 3D model by Ninma Oy. Source: Objaverse 1.0 / Sketchfab
Hackness Cross Full Res OM-D EM-1 12-40mm Raw
Hackness Cross full resolution This high resolution model incorporates digital lighting that can be 'moved around to cast shadows' to make it easier to view the instcriptions and scupltural details. To move the virtual lights around (on a Mac) press and hold the alt key and press the left mouse button and move the mouse around to shift the light source. Source: Objaverse 1.0 / Sketchfab
Stone Shaft Abrader High Res
On display at the Hutchings Museum Institute, Shaft Arbraders were used for sanding and smoothing arrow shafts, similar to modern sand paper. 169 images, Canon EOS 80D, 35mm, F/16, ISO 100, Agisoft Metashape, Windows 10. Source: Objaverse 1.0 / Sketchfab
Vintage Letter Box Game Res
Here is my game res version of my vintage letter box. You can see that the sillohette is very readable but with a lower poly count compaired to the High res model. Source: Objaverse 1.0 / Sketchfab
Mechanical alphabet, TM1356 (Low res.)
Christopher Polhem (1661-1751) created the so-called mechanical alphabet in the years just before 1700. The wooden models illustrated the fundamentals of physics and mechanics and were intended to serve as an educational tool in teachings at the Laboratorium mechanicum established in 1697. After his death, the collection continued to serve as a didactic instrument and became part of the Swedish Royal Model Chamber. In 1925, the collection of 31 models was deposited at the newly established National Museum of Science and Technology. [TM1356](https://digitaltmuseum.se/021026346886/mekaniskt-alfabet-modell?i=42&aq=owner%3A%22S-TEK%22+text%3A%22polhem%22"tm1356") (TEKS0014660) Created in RealityCapture by Fredrik Olsson from 108 images in 00h:49m:22s. Please note: No post processing have been done, holes may occur in mesh. Read more about [Polhem]( https://en.wikipedia.org/wiki/Christopher_Polhem"polhem") on Wikipedia. Source: Objaverse 1.0 / Sketchfab
Segmentation Zoo Res-UNet models for Landsat-8 satellite imagery, Coast Train v1 Landsat-8 4-class subset.
<p><strong>Doodleverse/Segmentation Zoo models for Landsat-8 satellite imagery, Coast Train v1 Landsat-8 4-class subset.</strong></p> <p>These model data are based on the Coast Train v1 Landsat-8 labeled imagery subset. Models have been fitted to 4 different types of data</p> <p>1. NDWI (1 band): (g-nir)/(g+nir)</p> <p>2. MNDWI (1 band): (swir-g)/(swir+g)</p> <p>3. RGB (3 band): red, green, blue</p> <p>4. RGB-NIR-SWIR (5 band): red, green, blue, nir, swir</p> <p>Classes are: {0: water, 1: whitewater, 2:sediment, 3:other}. These classes have been remapped from the original 11 classes<br> </p> <p>These files are used in conjunction with Segmentation Zoo*</p> <p>For each model, there are 3 files:</p> <p>1. config file: this is the file that was used by Segmentation Gym** to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse.</p> <p> </p> <p>2. weights file: this is the file that was created by the Segmentation Gym** function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym** function `seg_images_in_folder.py` or the Segmentation Zoo* function `select_model_and_batch_process_folder.py` to segment a folder of images</p> <p> </p> <p>3. model card file: this is a json file containing the following fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata</p> <p> </p> <p>References</p> <p>* https://github.com/Doodleverse/segmentation_zoo</p> <p>** https://github.com/Doodleverse/segmentation_gym</p> <p> </p>
Doodleverse/Segmentation Zoo Res-UNet models for identifying coins in photos of sediment.
<p><strong>Doodleverse/Segmentation Zoo models for identifying coins in photos of sediment.</strong></p> <p>These model data are based on images of sand and coins and associated labels. Models have been fitted to the following types of data</p> <p>1. RGB (3 band): red, green, blue</p> <p>Classes are: {0: other, 1: coin}.</p> <p>These files are used in conjunction with Segmentation Zoo*</p> <p>For each model, there are 3 files with the same root name:</p> <p>1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym** to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse.</p> <p> </p> <p>2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym** function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym** function `seg_images_in_folder.py` or the Segmentation Zoo* function `select_model_and_batch_process_folder.py` to segment a folder of images</p> <p> </p> <p>3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model</p> <p> </p> <p>References</p> <p>* https://github.com/Doodleverse/segmentation_zoo</p> <p>** https://github.com/Doodleverse/segmentation_gym</p>
Doodleverse/Segmentation Zoo Res-UNet models for identifying water in oblique aerial photos of coasts.
<p><strong>Doodleverse/Segmentation Zoo Res-UNet models for identifying water in oblique aerial photos of coasts.</strong></p> <p>These model data are based on images of coasts and associated labels. Models have been fitted to the following types of data</p> <p>1. RGB (3 band): red, green, blue</p> <p>Classes are: {0: water, 1: land}.</p> <p>These files are used in conjunction with Segmentation Zoo*</p> <p>For each model, there are 3 files with the same root name:</p> <p>1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym** to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse.</p> <p> </p> <p>2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym** function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym** function `seg_images_in_folder.py` or the Segmentation Zoo* function `select_model_and_batch_process_folder.py` to segment a folder of images</p> <p> </p> <p>3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model</p> <p> </p> <p>References</p> <p>* https://github.com/Doodleverse/segmentation_zoo</p> <p>** https://github.com/Doodleverse/segmentation_gym</p>
Doodleverse/Segmentation Zoo Res-UNet models for identifying water in Sentinel-2 MNDWI images of coasts.
<p><strong>Doodleverse/Segmentation Zoo Res-UNet models for identifying water in Sentinel-2 MNDWI images of coasts.</strong></p> <p><strong>Based on SWED*** data</strong></p> <p>https://openmldata.ukho.gov.uk/</p> <p>These Residual-UNet model data are based on images of coasts and associated labels. Models have been fitted to the following types of data</p> <p>1. MNDWI (1 band): mndwi</p> <p>MNDWI = (Green - SWIR) / (Green + SWIR)<br> Green = pixel values from the green band<br> SWIR = pixel values from the short-wave infrared band</p> <p>Reference: Xu, H. "Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery." International Journal of Remote Sensing 27, No. 14 (2006): 3025-3033." (ESRI, 2018)</p> <p>Classes are: {0: null, 1: water}.</p> <p>These files are used in conjunction with Segmentation Zoo*</p> <p>For each model, there are 3 files with the same root name:</p> <p>1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym** to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse.</p> <p> </p> <p>2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym** function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym** function `seg_images_in_folder.py` or the Segmentation Zoo* function `select_model_and_batch_process_folder.py` to segment a folder of images</p> <p> </p> <p>3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model</p> <p>References</p> <p>* https://github.com/Doodleverse/segmentation_zoo</p> <p>** https://github.com/Doodleverse/segmentation_gym</p> <p>*** https://www.sciencedirect.com/science/article/abs/pii/S0034425722001584</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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OpenNeuro
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