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pomegranate-farming-monitoring-system
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TMP2023-229
pomegranate-farming-monitoring-system
Commits
252627c4
Commit
252627c4
authored
Nov 10, 2023
by
asus
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Training/Disease Detection/Disease Classification VGG16.ipynb
...ning/Disease Detection/Disease Classification VGG16.ipynb
+788
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Training/Disease Detection/Disease Confirmation-VGG16.ipynb
Training/Disease Detection/Disease Confirmation-VGG16.ipynb
+902
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Training/Disease Detection/Image increase.ipynb
Training/Disease Detection/Image increase.ipynb
+105
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Training/Disease Detection/image resize.ipynb
Training/Disease Detection/image resize.ipynb
+148
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Training/Disease Detection/Disease Classification VGG16.ipynb
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252627c4
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Training/Disease Detection/Disease Confirmation-VGG16.ipynb
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252627c4
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Training/Disease Detection/Image increase.ipynb
0 → 100644
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252627c4
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "72ba86ae",
"metadata": {},
"outputs": [
{
"ename": "OSError",
"evalue": "cannot write mode RGBA as JPEG",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\PIL\\JpegImagePlugin.py:643\u001b[0m, in \u001b[0;36m_save\u001b[1;34m(im, fp, filename)\u001b[0m\n\u001b[0;32m 642\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 643\u001b[0m rawmode \u001b[38;5;241m=\u001b[39m \u001b[43mRAWMODE\u001b[49m\u001b[43m[\u001b[49m\u001b[43mim\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m]\u001b[49m\n\u001b[0;32m 644\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
"\u001b[1;31mKeyError\u001b[0m: 'RGBA'",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn [2], line 32\u001b[0m\n\u001b[0;32m 30\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, transformed_image \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(transformed_images):\n\u001b[0;32m 31\u001b[0m transformed_image_path \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(new_folder_path, \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfilename\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_transformed_\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mi\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.jpg\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m---> 32\u001b[0m \u001b[43mtransformed_image\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msave\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtransformed_image_path\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 34\u001b[0m \u001b[38;5;66;03m# Increment the number of processed images and check if we've processed 400 images\u001b[39;00m\n\u001b[0;32m 35\u001b[0m processed_images \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n",
"File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\PIL\\Image.py:2431\u001b[0m, in \u001b[0;36mImage.save\u001b[1;34m(self, fp, format, **params)\u001b[0m\n\u001b[0;32m 2428\u001b[0m fp \u001b[38;5;241m=\u001b[39m builtins\u001b[38;5;241m.\u001b[39mopen(filename, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mw+b\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 2430\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m-> 2431\u001b[0m \u001b[43msave_handler\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 2432\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[0;32m 2433\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m open_fp:\n",
"File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\PIL\\JpegImagePlugin.py:646\u001b[0m, in \u001b[0;36m_save\u001b[1;34m(im, fp, filename)\u001b[0m\n\u001b[0;32m 644\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m 645\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot write mode \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mim\u001b[38;5;241m.\u001b[39mmode\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m as JPEG\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m--> 646\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m(msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[0;32m 648\u001b[0m info \u001b[38;5;241m=\u001b[39m im\u001b[38;5;241m.\u001b[39mencoderinfo\n\u001b[0;32m 650\u001b[0m dpi \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mround\u001b[39m(x) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m info\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdpi\u001b[39m\u001b[38;5;124m\"\u001b[39m, (\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m))]\n",
"\u001b[1;31mOSError\u001b[0m: cannot write mode RGBA as JPEG"
]
}
],
"source": [
"from PIL import Image\n",
"import os\n",
"\n",
"# Path to the existing folder with image files\n",
"existing_folder_path = r\"C:\\Users\\asus\\Desktop\\New folder\"\n",
"\n",
"# Create a new folder to store the transformed images\n",
"new_folder_path =r\"C:\\Users\\asus\\Desktop\\New folder (2)\"\n",
"if not os.path.exists(new_folder_path):\n",
" os.makedirs(new_folder_path)\n",
"\n",
"# Loop through all image files in the existing folder\n",
"processed_images = 0\n",
"for filename in os.listdir(existing_folder_path):\n",
" # Check if the file is an image file\n",
" if filename.endswith(\".jpg\") or filename.endswith(\".png\"):\n",
" # Open the existing image\n",
" existing_image_path = os.path.join(existing_folder_path, filename)\n",
" existing_image = Image.open(existing_image_path)\n",
"\n",
" # Apply some transformations to the image\n",
" transformed_images = []\n",
" for i in range(5):\n",
" # Example transformations - you can modify these to fit your needs\n",
" transformed_image = existing_image.rotate(90*i)\n",
" transformed_image = transformed_image.transpose(Image.FLIP_LEFT_RIGHT)\n",
" transformed_images.append(transformed_image)\n",
"\n",
" # Save the transformed images to the new folder\n",
" for i, transformed_image in enumerate(transformed_images):\n",
" transformed_image_path = os.path.join(new_folder_path, f\"{filename}_transformed_{i}.jpg\")\n",
" transformed_image.save(transformed_image_path)\n",
"\n",
" # Increment the number of processed images and check if we've processed 400 images\n",
" processed_images += 1\n",
" if processed_images == 400:\n",
" break\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3026991e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "e4e351af",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Training/Disease Detection/image resize.ipynb
0 → 100644
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252627c4
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