{"id":24116130,"url":"https://github.com/lgariv/maskpass","last_synced_at":"2026-05-08T07:34:35.261Z","repository":{"id":139874348,"uuid":"326395425","full_name":"lgariv/MaskPass","owner":"lgariv","description":"Electronic Engineering final project","archived":false,"fork":false,"pushed_at":"2021-07-30T16:03:03.000Z","size":22547,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-31T14:04:53.011Z","etag":null,"topics":["face-mask","face-mask-classification","keras","opencv","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lgariv.png","metadata":{"files":{"readme":"README-he.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-01-03T11:53:21.000Z","updated_at":"2021-07-30T16:03:16.000Z","dependencies_parsed_at":null,"dependency_job_id":"384ed12a-1b0f-43a9-b6cf-a2f5965729ee","html_url":"https://github.com/lgariv/MaskPass","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/lgariv/MaskPass","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgariv%2FMaskPass","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgariv%2FMaskPass/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgariv%2FMaskPass/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgariv%2FMaskPass/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lgariv","download_url":"https://codeload.github.com/lgariv/MaskPass/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgariv%2FMaskPass/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32771094,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-08T02:36:36.067Z","status":"ssl_error","status_checked_at":"2026-05-08T02:36:07.210Z","response_time":54,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["face-mask","face-mask-classification","keras","opencv","tensorflow"],"created_at":"2025-01-11T06:15:29.304Z","updated_at":"2026-05-08T07:34:35.247Z","avatar_url":"https://github.com/lgariv.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# פרויקט גמר\n\n## שלב 1\n\n**אימון מודל לסיווג מסיכה ב-Google Colab (בעזרת GPU)**\n\n-   מודל מבוסס MobileNet V2:\n\n    [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1x3a_JSMoKCcjiKo2UGFiot2A4JVBdYar?usp=sharing)\n\n## שלב 2\n\n**התקנת מערכת הפעלה Raspberry Pi OS 64-bit על Raspberry Pi 4B**\n\n[יש להוריד את הגירסא האחרונה](https://downloads.raspberrypi.org/raspios_arm64/images/)\n\nמומלץ להתקין על כרטיס זיכרון או דיסק און קי באמצעות [Raspberry Pi Imager](https://www.raspberrypi.org/software/).\n\nלאחר ההתקנה על כרטיס הזיכרון, על מנת לקבל גישה ל-Raspberry Pi בלי לחברו למסך, מקלדת ועכבר חיצוניים יש ליצור קובץ טקסט חדש בשם `ssh` (באותיות קטנות) וללא סיומת בתיקיה הראשית.\n\nעל מנת לחבר את ה-Raspberry Pi לרשת האלחוטית המקומית שלנו, ניצור קובץ טקסט חדש שתוכנו:\n\n```txt\nctrl_interface=DIR=/var/run/wpa_supplicant GROUP=netdev\nupdate_config=1\ncountry=IL\n\nnetwork={\n  ssid=\"WiFi\"\n  psk=\"Password\"\n}\n```\n\nכאשר בתוך המרכאות הכפולות יש למלא את השם והסיסמא לרשת, בהתאמה.\n\nעל מנת להתחבר ל-Raspberry Pi על גבי SSH, נתחבר לאותה הרשת שהגדרנו ונבצע את הפקודה הבאה:\n\n```bash\nssh pi@raspberrypi.local\n```\n\nהפקודה תבקש סיסמא - הסיסמא ברירת המחדל היא `raspberry` (באותיות קטנות).\n\n## שלב 3\n\n**עדכונים**\n\nלאחר שה-Raspberry Pi נדלק, נבצע מספר פקודות על גבי SSH על מנת לוודא שהמערכת מעודכנת:\n\n```bash\nsudo apt update\nsudo apt full-upgrade -y\nsudo apt dist-upgrade\nsudo apt autoremove --purge\nsudo apt clean\n```\n\n## שלב 4\n\n**התקנת NumPy**\n\n```bash\npip3 install numpy\n```\n\n## שלב 5\n\n**התקנת OpenCV גירסא 4.5.0 (מותאם לארכיטקטורת `arm64`)**\n\n[מדריך של Q-engineering](https://qengineering.eu/install-opencv-4.5-on-raspberry-64-os.html)\n\n## שלב 6\n\n**התקנת TensorFlow Lite Runtime גירסא 2.5.0 (מותאם לארכיטקטורת `arm64`)**\n\n```bash\necho \"deb https://packages.cloud.google.com/apt coral-edgetpu-stable main\" | sudo tee /etc/apt/sources.list.d/coral-edgetpu.list\ncurl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -\nsudo apt-get update\nsudo apt-get install python3-tflite-runtime\n```\n\n[מקור: TendorFlow.org/lite](https://qengineering.eu/install-tensorflow-2.4.0-on-raspberry-64-os.html)\n\n## שלב 7\n\n**התקנת המסך MHS3528**\n\nבשורת הפקודה של ה-Raspberry Pi:\n\n```bash\nsudo rm -rf LCD-show\ngit clone https://github.com/goodtft/LCD-show.git\nchmod -R 755 LCD-show\ncd LCD-show/\nsudo ./MHS35-show\n```\n\n## שלב 8\n\n**הורדת הפרויקט**\n\nבשורת הפקודה של הRaspberry Pi:\n\n```bash\ngit clone https://github.com/lgariv/CollegeProject.git\n```\n\n## שלב 9\n\n**הורדת המודל לסיווג המסיכה מ-Google Colab**\n\nהעברה ל-Raspberry Pi, פקודה מהמחשב שאליו הורדנו את הקובץ:\n\n```cmd\nscp /path/to/model_quant.tflite pi@raspberrypi.local:/home/pi/CollegeProject/models/model_quant.tflite\n```\n\n## שלב 10\n\n**הפעלה**\n\nבשורת הפקודה של ה-Raspberry PI:\n\n```bash\ncd CollegeProject\npython3 door-model.py \u0026 python3 Object_detection_webcam_tflite.py \u0026\u0026 fg\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flgariv%2Fmaskpass","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flgariv%2Fmaskpass","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flgariv%2Fmaskpass/lists"}