Added result.json and classes.py file for Flower_Net

Flower_Net-CNN/classes.py

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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

Flower_Net-CNN/result.json

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+{"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. 
+
+}