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Added result.json and classes.py file for Flower_Net #26

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10 changes: 10 additions & 0 deletions Flower_Net-CNN/classes.py
Original file line number Diff line number Diff line change
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import torch.nn as nn

class ensemble_Net(nn.Module):
pass
class Flower_Net_1(nn.Module):
pass
class Flower_Net_2(nn.Module):
pass
class Flower_Net_3(nn.Module):
pass
14 changes: 14 additions & 0 deletions Flower_Net-CNN/result.json
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
{"Title": "Flower_Net",
"Tags": ["Computer Vision","CNN"],
"Architecture":"CNN-2D",
"Publisher": [["Aryaman Sriram","https://github.com/aryamansriram"],["Smoketrees","https://github.com/smoke-trees"]],
"Problem Domain": "Image",
"Model Format":"CNN Ensemble",
"Language": "English",
"Dataset": [["Flower Recognition","https://www.kaggle.com/alxmamaev/flowers-recognition"]],
"Link" : "https://drive.google.com/file/d/1wk2VXY38r10EK4ApebvrtMGR0XnK_13X/view?usp=sharing",
"Usage": "usage.html",
"Input Shape": [["224X224"]],
"Output Shape": [["1X5"]],
"Description": "Flower_Net is a custom ensemble architecture consisting of 3 convolutional neural networks consisting of filters of different sizes which aims to learn as many features as it can from around 4000 images of flowers and classify five different categories of flowers."
}