Initial codebase (#1)

* Add project code

* Logger improvements

* Improvements to web demo code

* added create_wlasl_landmarks_dataset.py and xtract_mediapipe_landmarks.py

* Fix rotation augmentation

* fixed error in docstring, and removed unnecessary replace -1 -> 0

* Readme updates

* Share base notebooks

* Add notebooks and unify for different datasets

* requirements update

* fixes

* Make evaluate more deterministic

* Allow training with clearml

* refactor preprocessing and apply linter

* Minor fixes

* Minor notebook tweaks

* Readme updates

* Fix PR comments

* Remove unneeded code

* Add banner to Readme

---------

Co-authored-by: Gabriel Lema <gabriel.lema@xmartlabs.com>

train.sh

@@ -0,0 +1,24 @@
+#!/bin/sh
+python -m train \
+	--save_checkpoints_every -1 \
+    --experiment_name "augment_rotate_75_x8" \
+    --epochs 10 \
+	--optimizer "SGD" \
+	--lr 0.001 \
+    --batch_size 32 \
+	--dataset_name "wlasl" \
+	--training_set_path "WLASL100_train.csv" \
+	--validation_set_path "WLASL100_test.csv" \
+	--vector_length 32 \
+	--epoch_iters -1 \
+	--scheduler_factor 0 \
+	--hard_triplet_mining "in_batch" \
+	--filter_easy_triplets \
+	--triplet_loss_margin 1 \
+	--dropout 0.2 \
+	--start_mining_hard=200 \
+	--hard_mining_pre_batch_multipler=16 \
+	--hard_mining_pre_batch_mining_count=5 \
+	--augmentations_prob=0.75 \
+	--hard_mining_scheduler_triplets_threshold=0 \
+	# --normalize_embeddings \