updated README, added requirements.txt

Phase 1/Plots/README.md

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+# Plots generated by task_3.ipynb in show_similar_images()

Phase 1/README.md

@@ -7,3 +7,25 @@ Getting started: PyTorch, Caltech101 dataset, ResNet50 and similarity measures
   - Color moments - Pearson (faces especially)
   - Histogram of oriented gradients (HOG) - Cosine similarity
   - ResNet50 (avgpool, layer3, fc) - unsatisfactory results for all, simply used euclidean
+
+## Requirements
+
+Install packages from requirements.txt (might not be complete)
+
+## Task 1 - task_1.ipynb
+
+After installing, run all cells in the notebook. There will be a prompt to give input for image ID. Range is 0 to 8677
+
+## Task 2 - task_2.ipynb
+
+Dataset processing and storage to database. Ensure MongoDB server is running, modify connection URI as needed if running on Atlas
+
+## Task 3 - task_3.ipynb
+
+Execute all cells till before the "Target images" markdown cell. There will be four prompts to give input for:
+
+- **Image ID**: integer, 0 to 8677
+- No. of similar images needed, **k**: positive integer
+- **Feature model** - one of ["cm", "hog", "avgpool", "layer3", "fc"]
+  - _Note: only hog is applicable for all images. Others cannot be used for grayscale images_
+- **Similarity/distance measure** - one of ["euclidean", "cosine", "pearson"]

Phase 1/requirements.txt

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+numpy
+scipy
+scikit-learn
+scikit-image
+opencv-python
+matplotlib
+torch
+torchvision
+pymongo[srv]
+ipython
+notebook
+ipykernel
+