{"id":24116175,"url":"https://github.com/camille-maslin/simulfcimage","last_synced_at":"2026-02-05T04:02:35.630Z","repository":{"id":269603276,"uuid":"907803204","full_name":"Camille-Maslin/SimulFCImage","owner":"Camille-Maslin","description":"🔍 SimulFCImage: A professional multispectral image processing application developed for ImViA Laboratory.","archived":false,"fork":false,"pushed_at":"2024-12-24T18:01:06.000Z","size":4107,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-03T01:51:10.428Z","etag":null,"topics":["academic-project","computer-vision","data-analysis","gui-application","image-processing","image-viewer","multispectral-images","pyqt5","python","scientific-visualization","spectral-analysis"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Camille-Maslin.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2024-12-24T12:30:14.000Z","updated_at":"2025-01-02T15:47:27.000Z","dependencies_parsed_at":"2024-12-24T19:28:35.559Z","dependency_job_id":null,"html_url":"https://github.com/Camille-Maslin/SimulFCImage","commit_stats":null,"previous_names":["camille-maslin/simulfcimage"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Camille-Maslin/SimulFCImage","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Camille-Maslin%2FSimulFCImage","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Camille-Maslin%2FSimulFCImage/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Camille-Maslin%2FSimulFCImage/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Camille-Maslin%2FSimulFCImage/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Camille-Maslin","download_url":"https://codeload.github.com/Camille-Maslin/SimulFCImage/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Camille-Maslin%2FSimulFCImage/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29110573,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-05T03:44:17.043Z","status":"ssl_error","status_checked_at":"2026-02-05T03:44:12.077Z","response_time":65,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: 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":["academic-project","computer-vision","data-analysis","gui-application","image-processing","image-viewer","multispectral-images","pyqt5","python","scientific-visualization","spectral-analysis"],"created_at":"2025-01-11T06:15:43.281Z","updated_at":"2026-02-05T04:02:35.608Z","avatar_url":"https://github.com/Camille-Maslin.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1\u003eSimulFCImage - LaBabaTcheam C1\u003c/h1\u003e\n\n\u003ch2\u003eProject Overview\u003c/h2\u003e\n\u003cp\u003eSimulFCImage is a sophisticated Python application designed for multispectral image analysis and visualization. It transforms complex multispectral data into comprehensible color representations through various simulation methods, making it an invaluable tool for research and analysis.\u003c/p\u003e\n\n\u003ch2\u003eKey Features\u003c/h2\u003e\n\n\u003ch3\u003e1. Human Vision Simulation\u003c/h3\u003e\n\u003cp\u003eOffers two distinct approaches to simulate human color perception:\u003c/p\u003e\n\n\u003ch4\u003eVersion 1 (Classic):\u003c/h4\u003e\n\u003cp\u003eUses Gaussian approximations to simulate human cone sensitivity:\n- Approximates L, M, S cone responses using Gaussian functions\n- Provides a simplified but efficient approach to color reproduction\n- Suitable for quick visualization where absolute accuracy isn't critical\u003c/p\u003e\n\n\u003ch4\u003eVersion 2 (Advanced):\u003c/h4\u003e\n\u003cp\u003eBased on precise scientific standards:\n- Utilizes CIE 1931 color matching functions\n- References Stockman \u0026 Sharpe (2000) cone fundamentals:\n  - L-cones (red): peak at 566.8nm\n  - M-cones (green): peak at 541.2nm\n  - S-cones (blue): peak at 441.8nm\n- Performs spectral interpolation for accurate wavelength matching\n- Implements proper color space transformations\u003c/p\u003e\n\n\u003ch3\u003e2. Custom Band Mapping (\"False Color\")\u003c/h3\u003e\n\u003cp\u003eEnables manual assignment of specific spectral bands to RGB channels, allowing users to:\n- Highlight features invisible to the human eye\n- Emphasize specific wavelength ranges\n- Create custom visualization schemes for analysis\u003c/p\u003e\n\n\u003ch3\u003e3. Bee Vision Simulation\u003c/h3\u003e\n\u003cp\u003eModels bee photoreceptor response based on scientific research (Peitsch et al., 1992):\n- UV receptor: peak at 344nm (±1nm)\n- Blue receptor: peak at 436nm (±3nm)\n- Green receptor: peak at 544nm (±3nm)\nProvides insights into how bees perceive the multispectral image.\u003c/p\u003e\n\n\u003ch3\u003e4. Color Vision Deficiency Simulation\u003c/h3\u003e\n\u003cp\u003eSimulates various types of color vision deficiencies based on Brettel et al. (1997) and Machado et al. (2009):\n- Deuteranopia (green-blind)\n- Protanopia (red-blind)\n- Tritanopia (blue-blind)\n- Deuteranomaly (green-weak)\n- Protanomaly (red-weak)\n- Tritanomaly (blue-weak)\n- Achromatopsia (complete color blindness)\u003c/p\u003e\n\n\u003ch2\u003eInstallation Guide\u003c/h2\u003e\n\n\u003ch3\u003eOption 1: Pre-compiled Application\u003c/h3\u003e\n1. Download SimulFCImage setup.exe from Google Drive ( https://drive.google.com/drive/folders/1uRv_wMsNEgHqScpr94n4Br1E7VYtcmYx?usp=sharing ) \u003cbr\u003e\n2. Launch SimulFCImage setup.exe \u003cbr\u003e\n3. (Optional) Download sample multispectral images from the \"Teeth\" folder\n\n\u003ch3\u003eOption 2: Building from Source\u003c/h3\u003e\n1. Clone the repository \u003cbr\u003e\n2. Install dependencies:\n\n```bash\npip install Pillow numpy cx_Freeze\n```\n3. Run Program.py to compile and launch the application\n\n\u003ch2\u003eUsage Guide\u003c/h2\u003e\n\n\u003ch3\u003eLoading Images\u003c/h3\u003e\n1. Click \"Import an image\" on the upper band \u003cbr\u003e\n2. Select a multispectral image (.tiff format) \u003cbr\u003e\n3. Import the corresponding metadata file (.txt) \u003cbr\u003e\n4. Navigate through bands using \"Previous\" and \"Next\" buttons\n\n\u003cimg src=\"README_ASSETS/MainWindowLoadSave.png\" width=\"1024\"/\u003e\n\u003cimg src=\"README_ASSETS/MainWindowSimulation.png\" width=\"1024\"/\u003e\n\n\u003ch3\u003eGenerating Color Images\u003c/h3\u003e\n1. Click \"Generate a color image\" on the upper band \u003cbr\u003e\n2. Select a simulation method:\n   - True Color (Human Vision V1 or V2)\n   - RGB Bands Choice (Custom Mapping)\n   - Bee Vision\n   - Color Vision Deficiency \u003cbr\u003e\n3. Configure method-specific parameters if required \u003cbr\u003e\n4. Click \"Simulate\" to generate the image\n\n\u003cimg src=\"README_ASSETS/MainWindowSimulation.png\" width=\"1024\"/\u003e\n\n\u003ch3\u003eResults and Export\u003c/h3\u003e\n- The generated image appears alongside the original\n- Use the \"Save\" button to export in various formats (.png, .jpg, .tif)\n\n\u003cimg src=\"README_ASSETS/MainWindowFinal.png\" width=\"1024\"/\u003e\n\n\u003ch2\u003eProject Architecture\u003c/h2\u003e\n\n```bash\nS5_C1_LaBabaTcheam\n├─Exceptions\n│ └─...\n├─HMI\n│ ├─assets\n│ │ └─...\n│ ├─MainWindow.py\n│ └─SimulationChoiceWindow.py\n├─LogicLayer\n│ ├─Factory\n│ │ ├─CreateSimulating\n│ │ │ ├─ CreateBandChoiceSimulating.py\n│ │ │ ├─ CreateBeeSimulating.py\n│ │ │ ├─ CreateDaltonianSimulating.py\n│ │ │ ├─ CreateHumanSimulating.py\n│ │ │ └─ ICreateSimulator.py\n│ │ ├─Simulating\n│ │ │ ├─ BandChoiceSimulating.py\n│ │ │ ├─ BeeSimulating.py\n│ │ │ ├─ DaltonianSimulating.py\n│ │ │ ├─ HumanSimulating.py\n│ │ │ └─ SimulatingMethod.py\n│ └─└─SimulatorFactory.py\n│ ├─Band.py\n│ └─ImageMS.py\n├─Storage\n│ ├─FileManager.py\n│ └─ImageManager.py\n├─UnitTests\n│ └─...\n├─.gitignore\n├─Program.py\n├─README.md\n└─setup.py\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcamille-maslin%2Fsimulfcimage","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcamille-maslin%2Fsimulfcimage","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcamille-maslin%2Fsimulfcimage/lists"}