Merge pull request #6 from 20kaushik02/phase3_task3

Phase3 task 3 and 4

Phase 2/task_11.ipynb

@@ -1311,7 +1311,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

Phase 2/task_8.ipynb

@@ -432,7 +432,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

Phase 3/utils.py

@@ -0,0 +1,68 @@
+# All imports
+# Math
+import math
+import random
+import cv2
+import numpy as np
+from scipy.stats import pearsonr
+
+# from scipy.sparse.linalg import svds
+# from sklearn.decomposition import NMF
+from sklearn.decomposition import LatentDirichletAllocation
+
+# from sklearn.cluster import KMeans
+
+# Torch
+import torch
+import torchvision.transforms as transforms
+from torchvision.datasets import Caltech101
+from torchvision.models import resnet50, ResNet50_Weights
+
+import tensorly as tl
+
+# OS and env
+import json
+import os
+from os import getenv
+from dotenv import load_dotenv
+import warnings
+from joblib import dump, load
+
+load_dotenv()
+
+# MongoDB
+from pymongo import MongoClient
+
+# Visualizing
+import matplotlib.pyplot as plt
+
+
+
+valid_classification_methods = {
+    "m-nn": 1,
+    "decision-tree": 2,
+    "ppr": 3,
+}
+
+def getCollection(db, collection):
+    """Load feature descriptor collection from MongoDB"""
+    client = MongoClient("mongodb://localhost:27017")
+    return client[db][collection]
+
+
+def euclidean_distance_measure(img_1_fd, img_2_fd):
+    img_1_fd_reshaped = img_1_fd.flatten()
+    img_2_fd_reshaped = img_2_fd.flatten()
+
+    # Calculate Euclidean distance
+    return math.dist(img_1_fd_reshaped, img_2_fd_reshaped)
+
+
+valid_feature_models = {
+    "cm": "cm_fd",
+    "hog": "hog_fd",
+    "avgpool": "avgpool_fd",
+    "layer3": "layer3_fd",
+    "fc": "fc_fd",
+    "resnet": "resnet_fd",
+}