├── snow.jpg ├── prediction_image.jpg ├── prediction_image_2.jpg ├── ai_weather_detector_emirhan_artificial_intelligence.png ├── ai_weather_detector_emirhan_artificial_intelligence.spec ├── README.md └── ai_weather_detector_emirhan_artificial_intelligence.py /snow.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/emirhanai/AI-Weather-Detection-with-.EXE-Application-Neural-Networks-Software-100-Originally--99-Accura/HEAD/snow.jpg -------------------------------------------------------------------------------- /prediction_image.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/emirhanai/AI-Weather-Detection-with-.EXE-Application-Neural-Networks-Software-100-Originally--99-Accura/HEAD/prediction_image.jpg -------------------------------------------------------------------------------- /prediction_image_2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/emirhanai/AI-Weather-Detection-with-.EXE-Application-Neural-Networks-Software-100-Originally--99-Accura/HEAD/prediction_image_2.jpg -------------------------------------------------------------------------------- /ai_weather_detector_emirhan_artificial_intelligence.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/emirhanai/AI-Weather-Detection-with-.EXE-Application-Neural-Networks-Software-100-Originally--99-Accura/HEAD/ai_weather_detector_emirhan_artificial_intelligence.png -------------------------------------------------------------------------------- /ai_weather_detector_emirhan_artificial_intelligence.spec: -------------------------------------------------------------------------------- 1 | # -*- mode: python ; coding: utf-8 -*- 2 | 3 | 4 | block_cipher = None 5 | 6 | 7 | a = Analysis(['ai_weather_detector_emirhan.py'], 8 | pathex=['C:\\Users\\emirhan.bulut\\pythonProject13'], 9 | binaries=['numpy','cv2','tensorflow'], 10 | datas=[], 11 | hiddenimports=['numpy','cv2','tensorflow'], 12 | hookspath=[], 13 | hooksconfig={}, 14 | runtime_hooks=[], 15 | excludes=[], 16 | win_no_prefer_redirects=False, 17 | win_private_assemblies=False, 18 | cipher=block_cipher, 19 | noarchive=False) 20 | pyz = PYZ(a.pure, a.zipped_data, 21 | cipher=block_cipher) 22 | 23 | exe = EXE(pyz, 24 | a.scripts, 25 | a.binaries, 26 | a.zipfiles, 27 | a.datas, 28 | [], 29 | name='ai_weather_detector_emirhan', 30 | debug=False, 31 | bootloader_ignore_signals=False, 32 | strip=False, 33 | upx=True, 34 | upx_exclude=[], 35 | runtime_tmpdir=None, 36 | console=True, 37 | disable_windowed_traceback=False, 38 | target_arch=None, 39 | codesign_identity=None, 40 | entitlements_file=None ) 41 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # **AI Weather Detection with .EXE Application - Neural Networks Software - %100 Originally - %99 Accuracy** 2 | AI Weather Detection software is an original artificial intelligence system, whose image-based algorithm and model was created by me, working with 99% accuracy. The software has been converted to .EXE file format for the convenience of humans. It will automatically connect to the External Camera and just press the SPACE button (For taking pictures). The sample forecast data and artificial intelligence brain (model) were shared by me as open source. I am proud to share innovative software for you. This software is available as open source for free for all humanity. 3 | 4 | Note: Exe app is installed via Kaggle (High file size): https://www.kaggle.com/emirhanai/ai-weather-detector-exe-application 5 | 6 | Kind regards, 7 | 8 | Emirhan BULUT 9 | 10 | AI Inventor 11 | 12 | ###**The coding language used:** 13 | 14 | `Python 3.9.8` 15 | 16 | ###**Libraries Used:** 17 | 18 | `TensorFlow` 19 | 20 | `Keras` 21 | 22 | `OpenCV` 23 | 24 | `PyInstaller` 25 | 26 | `NumPy` 27 | 28 | AI Weather Detection with .EXE Application - Neural Networks Software - %100 Originally - %99 Accuracy 31 | 32 | ### **Developer Information:** 33 | 34 | Name-Surname: **Emirhan BULUT** 35 | 36 | Contact (Email) : **emirhan@isap.solutions** 37 | 38 | LinkedIn : **[https://www.linkedin.com/in/artificialintelligencebulut/][LinkedinAccount]** 39 | 40 | [LinkedinAccount]: https://www.linkedin.com/in/artificialintelligencebulut/ 41 | 42 | Kaggle: **[https://www.kaggle.com/emirhanai][Kaggle]** 43 | 44 | Official Website: **[https://www.emirhanbulut.com.tr][OfficialWebSite]** 45 | 46 | [Kaggle]: https://www.kaggle.com/emirhanai 47 | 48 | [OfficialWebSite]: https://www.emirhanbulut.com.tr 49 | -------------------------------------------------------------------------------- /ai_weather_detector_emirhan_artificial_intelligence.py: -------------------------------------------------------------------------------- 1 | import cv2 2 | import numpy as np 3 | from tensorflow.keras.models import load_model 4 | 5 | cam = cv2.VideoCapture(1) 6 | 7 | cv2.namedWindow("Weather Detection AI Software - Emirhan BULUT") 8 | 9 | while True: 10 | ret, frame = cam.read() 11 | if not ret: 12 | print("failed to grab frame") 13 | break 14 | cv2.imshow("test", frame) 15 | 16 | k = cv2.waitKey(1) 17 | if k % 256 == 27: 18 | # ESC pressed 19 | print("Escape hit, closing...") 20 | break 21 | elif k % 256 == 32: 22 | # SPACE pressed 23 | img_name = "prediction_image_3.jpg" 24 | cv2.imwrite(img_name, frame) 25 | print("{} written!".format(img_name)) 26 | break 27 | 28 | cam.release() 29 | cv2.destroyAllWindows() 30 | 31 | img_name = cv2.imread("prediction_image_3.jpg") 32 | 33 | img_name = img_name / 255 34 | img_name = cv2.resize(img_name, (128, 128)) 35 | img_name = np.reshape(img_name, [1, 128, 128, 3]) 36 | 37 | model = load_model("model_emirhan.h5") 38 | 39 | prediction = model.predict(img_name) 40 | 41 | font = cv2.FONT_HERSHEY_SIMPLEX 42 | org = (10, 30) 43 | fontScale = 1 44 | color = (228, 31, 36) 45 | thickness = 4 46 | 47 | print(prediction) 48 | if "{0}".format(prediction[0].max()) == "{0}".format(prediction[0][0]): 49 | prediction = "Prediction: Cloudy" 50 | elif "{0}".format(prediction[0].max()) == "{0}".format(prediction[0][1]): 51 | prediction = "Prediction: Rainy" 52 | elif "{0}".format(prediction[0].max()) == "{0}".format(prediction[0][2]): 53 | prediction = "Prediction: Shine" 54 | elif "{0}".format(prediction[0].max()) == "{0}".format(prediction[0][3]): 55 | prediction = "Prediction: Snowy" 56 | elif "{0}".format(prediction[0].max()) == "{0}".format(prediction[0][4]): 57 | prediction = "Prediction: Sunrise" 58 | 59 | img_name = cv2.imread("prediction_image_3.jpg") 60 | 61 | cv2.putText(img_name, prediction, org, font, 62 | fontScale, color, thickness, cv2.LINE_4) 63 | 64 | text = "Weather AI Detection" 65 | text1 = "by Emirhan BULUT" 66 | 67 | cv2.putText(img_name, text, (10, 60), font, 68 | fontScale, color, thickness, cv2.LINE_4) 69 | 70 | cv2.putText(img_name, text1, (10, 90), font, 71 | fontScale, color, thickness, cv2.LINE_4) 72 | 73 | cv2.imwrite("prediction_image_3.jpg", img_name) --------------------------------------------------------------------------------