From 8a40c3221d603e6eb04ed7a0123fb7d6c22d9112 Mon Sep 17 00:00:00 2001 From: gdamms Date: Mon, 28 Mar 2022 17:43:19 +0200 Subject: [PATCH] feat: debut apport Co-authored-by: Laurent --- docs/RAPPORT_0.html | 135 ++++++++++++++++++++++++++++++++++++++++ docs/RAPPORT_0.md | 54 ++++++++++++++++ docs/demo_datas.gif | Bin 0 -> 1519190 bytes docs/demo_datas/0_0.jpg | Bin 0 -> 19201 bytes docs/demo_datas/0_1.jpg | Bin 0 -> 15564 bytes docs/demo_datas/0_2.jpg | Bin 0 -> 17757 bytes docs/demo_datas/0_3.jpg | Bin 0 -> 16434 bytes docs/demo_datas/0_4.jpg | Bin 0 -> 18508 bytes docs/demo_datas/0_5.jpg | Bin 0 -> 17892 bytes docs/demo_datas/0_6.jpg | Bin 0 -> 18810 bytes docs/demo_datas/0_7.jpg | Bin 0 -> 19291 bytes docs/demo_datas/0_8.jpg | Bin 0 -> 19259 bytes docs/demo_datas/0_9.jpg | Bin 0 -> 19414 bytes docs/demo_datas/1_0.jpg | Bin 0 -> 14886 bytes docs/demo_datas/1_1.jpg | Bin 0 -> 17413 bytes docs/demo_datas/1_2.jpg | Bin 0 -> 17272 bytes docs/demo_datas/1_3.jpg | Bin 0 -> 17000 bytes docs/demo_datas/1_4.jpg | Bin 0 -> 17863 bytes docs/demo_datas/1_5.jpg | Bin 0 -> 18068 bytes docs/demo_datas/1_6.jpg | Bin 0 -> 18893 bytes docs/demo_datas/1_7.jpg | Bin 0 -> 20199 bytes docs/demo_datas/1_8.jpg | Bin 0 -> 19707 bytes docs/demo_datas/1_9.jpg | Bin 0 -> 19210 bytes docs/demo_datas/2_0.jpg | Bin 0 -> 17508 bytes docs/demo_datas/2_1.jpg | Bin 0 -> 17662 bytes docs/demo_datas/2_2.jpg | Bin 0 -> 15303 bytes docs/demo_datas/2_3.jpg | Bin 0 -> 16397 bytes docs/demo_datas/2_4.jpg | Bin 0 -> 17442 bytes docs/demo_datas/2_5.jpg | Bin 0 -> 17049 bytes docs/demo_datas/2_6.jpg | Bin 0 -> 18366 bytes docs/demo_datas/2_7.jpg | Bin 0 -> 19088 bytes docs/demo_datas/2_8.jpg | Bin 0 -> 20240 bytes docs/demo_datas/2_9.jpg | Bin 0 -> 19411 bytes docs/demo_datas/3_0.jpg | Bin 0 -> 15522 bytes docs/demo_datas/3_1.jpg | Bin 0 -> 18404 bytes docs/demo_datas/3_2.jpg | Bin 0 -> 16971 bytes docs/demo_datas/3_3.jpg | Bin 0 -> 17611 bytes docs/demo_datas/3_4.jpg | Bin 0 -> 17315 bytes docs/demo_datas/3_5.jpg | Bin 0 -> 17767 bytes docs/demo_datas/3_6.jpg | Bin 0 -> 17451 bytes docs/demo_datas/3_7.jpg | Bin 0 -> 18645 bytes docs/demo_datas/3_8.jpg | Bin 0 -> 19531 bytes docs/demo_datas/3_9.jpg | Bin 0 -> 18490 bytes src/main.py | 2 +- 44 files changed, 190 insertions(+), 1 deletion(-) create mode 100644 docs/RAPPORT_0.html create mode 100644 docs/RAPPORT_0.md create mode 100644 docs/demo_datas.gif create mode 100644 docs/demo_datas/0_0.jpg create mode 100644 docs/demo_datas/0_1.jpg create mode 100644 docs/demo_datas/0_2.jpg create mode 100644 docs/demo_datas/0_3.jpg create mode 100644 docs/demo_datas/0_4.jpg create mode 100644 docs/demo_datas/0_5.jpg create mode 100644 docs/demo_datas/0_6.jpg create mode 100644 docs/demo_datas/0_7.jpg create mode 100644 docs/demo_datas/0_8.jpg create mode 100644 docs/demo_datas/0_9.jpg create mode 100644 docs/demo_datas/1_0.jpg create mode 100644 docs/demo_datas/1_1.jpg create mode 100644 docs/demo_datas/1_2.jpg create mode 100644 docs/demo_datas/1_3.jpg create mode 100644 docs/demo_datas/1_4.jpg create mode 100644 docs/demo_datas/1_5.jpg create mode 100644 docs/demo_datas/1_6.jpg create mode 100644 docs/demo_datas/1_7.jpg create mode 100644 docs/demo_datas/1_8.jpg create mode 100644 docs/demo_datas/1_9.jpg create mode 100644 docs/demo_datas/2_0.jpg create mode 100644 docs/demo_datas/2_1.jpg create mode 100644 docs/demo_datas/2_2.jpg create mode 100644 docs/demo_datas/2_3.jpg create mode 100644 docs/demo_datas/2_4.jpg create mode 100644 docs/demo_datas/2_5.jpg create mode 100644 docs/demo_datas/2_6.jpg create mode 100644 docs/demo_datas/2_7.jpg create mode 100644 docs/demo_datas/2_8.jpg create mode 100644 docs/demo_datas/2_9.jpg create mode 100644 docs/demo_datas/3_0.jpg create mode 100644 docs/demo_datas/3_1.jpg create mode 100644 docs/demo_datas/3_2.jpg create mode 100644 docs/demo_datas/3_3.jpg create mode 100644 docs/demo_datas/3_4.jpg create mode 100644 docs/demo_datas/3_5.jpg create mode 100644 docs/demo_datas/3_6.jpg create mode 100644 docs/demo_datas/3_7.jpg create mode 100644 docs/demo_datas/3_8.jpg create mode 100644 docs/demo_datas/3_9.jpg diff --git a/docs/RAPPORT_0.html b/docs/RAPPORT_0.html new file mode 100644 index 0000000..e7953d4 --- /dev/null +++ b/docs/RAPPORT_0.html @@ -0,0 +1,135 @@ +

Model +classification in Rocket League Sideswipe

+

Laurent Fainsin Damien Guillotin Pierre-Eliot Jourdan

+

Lien vers notre dépot +gitlab

+

Description

+

Le but de ce projet est de permettre la reconnaissance +(classification) de voitures dans le jeu vidéo mobile Rocket League +Sideswipe, et ce peu importe les accessoires équipés tels que les roues, +les chapeaux, les stickers, les couleurs…

+

Méthodolgie d’acquisition +du dataset

+

Pour acquérir les 400 000 images de notre dataset, nous avons +simplement écrit un script capable d’automatiser la customisation des +modèles ainsi que la prise de screenshots. Il nous aura fallu environ 18 +heures pour constituer notre dataset.

+

Notre dataset est un dossier contenant toutes nos images et une base +de données sqlite3 faisant le lien entre les noms de nos screenshots +(des uuids) et les paramètre de la voiture dans l’image.

+

Par exemple ec7d32da-ad24-11ec-813b-e0d4e8390134.jpg +correspond au modèle de voiture 2 (la werewolf) à la team 0 (les bleus), +à la couleur primaire 50%, à la couleur secondaire 0%, au chapeau n°12 +(), au sticker n°1 (), à la +roue n°4 () et à la 3ème rotation.

+

Voici l’image associée :

+

+

Méthodologie

+ +

-> Voir la doc de tensorflow.

+

Pronostic

+

Si l’on décide d’évaluer le réseau sur des voitures avec une rotation +qui est la même que lors de l’aquisition des données, le résultat +devrait être plus que correct mais si l’on évalue le réseau sur une +rotation différente, c’est la que les problèmes peuvent arriver, il se +peut que l’on sur-apprenne la discretion de nos rotations.

+

Chargement de nos données

+ +

Exemple du dataset

+

+ +++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
RotationOctaneAfterShockWerewolfBreakout
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diff --git a/docs/RAPPORT_0.md b/docs/RAPPORT_0.md new file mode 100644 index 0000000..e06bfa5 --- /dev/null +++ b/docs/RAPPORT_0.md @@ -0,0 +1,54 @@ +# Model classification in Rocket League Sideswipe + +Laurent Fainsin -- +Damien Guillotin -- +Pierre-Eliot Jourdan + +Lien vers notre [dépot gitlab](https://git.inpt.fr/tocard-inc/enseeiht/projet-classification) + +## Description + +Le but de ce projet est de permettre la reconnaissance (classification) de voitures dans le jeu vidéo mobile Rocket League Sideswipe, et ce peu importe les accessoires équipés tels que les roues, les chapeaux, les stickers, les couleurs... + +## Méthodolgie d'acquisition du dataset + +Pour acquérir les 400 000 images de notre dataset, nous avons simplement écrit un script capable d'automatiser la customisation des modèles ainsi que la prise de screenshots. Il nous aura fallu environ 18 heures pour constituer notre dataset. + +Notre dataset est un dossier contenant toutes nos images et une base de données sqlite3 faisant le lien entre les noms de nos screenshots (des uuids) et les paramètre de la voiture dans l'image. + +Par exemple `ec7d32da-ad24-11ec-813b-e0d4e8390134.jpg` correspond au modèle de voiture 2 (la werewolf) à la team 0 (les bleus), à la couleur primaire 50%, à la couleur secondaire 0%, au chapeau n°12 (), au sticker n°1 (), à la roue n°4 () et à la 3ème rotation. + +Voici l'image associée : + +![](image_methodo.jpg) + +## Méthodologie + +* Description de votre méthodologie pour partitionner les images en ensembles d’entraı̂nement, de validation et de test. + +-> Voir la doc de tensorflow. + +## Pronostic + +Si l'on décide d'évaluer le réseau sur des voitures avec une rotation qui est la même que lors de l'aquisition des données, le résultat devrait être plus que correct mais si l'on évalue le réseau sur une rotation différente, c'est la que les problèmes peuvent arriver, il se peut que l'on sur-apprenne la discretion de nos rotations. + +## Chargement de nos données + +* Script de chargement de vos données. + +## Exemple du dataset + +![](demo_datas.gif) + +| Rotation | Octane | AfterShock | Werewolf | Breakout | +| :------- | :---------------------: | :---------------------: | :---------------------: | :---------------------: | +| 0 | ![](demo_datas/0_0.jpg) | ![](demo_datas/1_0.jpg) | ![](demo_datas/2_0.jpg) | ![](demo_datas/3_0.jpg) | +| 1 | ![](demo_datas/0_1.jpg) | ![](demo_datas/1_1.jpg) | ![](demo_datas/2_1.jpg) | ![](demo_datas/3_1.jpg) | +| 2 | ![](demo_datas/0_2.jpg) | ![](demo_datas/1_2.jpg) | ![](demo_datas/2_2.jpg) | ![](demo_datas/3_2.jpg) | +| 3 | ![](demo_datas/0_3.jpg) | ![](demo_datas/1_3.jpg) | ![](demo_datas/2_3.jpg) | ![](demo_datas/3_3.jpg) | +| 4 | ![](demo_datas/0_4.jpg) | ![](demo_datas/1_4.jpg) | ![](demo_datas/2_4.jpg) | ![](demo_datas/3_4.jpg) | +| 5 | 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