Python 2 -> 3 migration (#8525)

* Changed DELF installation instructions to be Python3 preferred

* Changed DELF landmark detection instructions to be Python3 preferred

* Changed DELF extraction and matching instructions to be Python3 preferred

* Changed DELF detect-to-retrieve instructions to be Python3 preferred

* Changed DELF training instructions to be Python3 preferred

* Added Python3 badge to DELF README

research/delf/DETECTION.md

@@ -44,7 +44,7 @@ threshold of 0.8, and produce visualizations.
 
 ```bash
 # From tensorflow/models/research/delf/delf/python/examples/
-python extract_boxes.py \
+python3 extract_boxes.py \
   --detector_path parameters/d2r_frcnn_20190411 \
   --detector_thresh 0.8 \
   --list_images_path list_images_detector.txt \

research/delf/EXTRACTION_MATCHING.md

@@ -44,7 +44,7 @@ features for the images `hertford_000056.jpg` and `oxford_000317.jpg`:
 
 ```bash
 # From tensorflow/models/research/delf/delf/python/examples/
-python extract_features.py \
+python3 extract_features.py \
   --config_path delf_config_example.pbtxt \
   --list_images_path list_images.txt \
   --output_dir data/oxford5k_features
@@ -56,7 +56,7 @@ After feature extraction, run this command to perform feature matching between
 the images `hertford_000056.jpg` and `oxford_000317.jpg`:
 
 ```bash
-python match_images.py \
+python3 match_images.py \
   --image_1_path data/oxford5k_images/hertford_000056.jpg \
   --image_2_path data/oxford5k_images/oxford_000317.jpg \
   --features_1_path data/oxford5k_features/hertford_000056.delf \
@@ -84,4 +84,4 @@ By default, skimage 0.13.XX or 0.14.1 is installed if you followed the
 instructions. According to
 [https://github.com/scikit-image/scikit-image/issues/3649#issuecomment-455273659]
 If you have scikit-image related issues, upgrading to a version above 0.14.1
-with `pip install -U scikit-image` should fix the issue
+with `pip3 install -U scikit-image` should fix the issue

research/delf/INSTALL_INSTRUCTIONS.md

@@ -3,6 +3,7 @@
 ### Tensorflow
 
 [![TensorFlow 2.1](https://img.shields.io/badge/tensorflow-2.1-brightgreen)](https://github.com/tensorflow/tensorflow/releases/tag/v2.1.0)
+[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)
 
 For detailed steps to install Tensorflow, follow the
 [Tensorflow installation instructions](https://www.tensorflow.org/install/). A
@@ -10,9 +11,9 @@ typical user can install Tensorflow using one of the following commands:
 
 ```bash
 # For CPU:
-pip install 'tensorflow'
+pip3 install 'tensorflow'
 # For GPU:
-pip install 'tensorflow-gpu'
+pip3 install 'tensorflow-gpu'
 ```
 
 ### TF-Slim
@@ -23,7 +24,7 @@ using previous versions which relied on tf.contrib (which is now deprecated).
 ```bash
 git clone git@github.com:google-research/tf-slim.git
 cd tf-slim
-pip install .
+pip3 install .
 ```
 
 Note that these commands assume you are cloning using SSH. If you are using
@@ -51,8 +52,8 @@ PATH_TO_PROTOC=`pwd`
 Install python library dependencies:
 
 ```bash
-pip install matplotlib numpy scikit-image scipy
-sudo apt-get install python-tk
+pip3 install matplotlib numpy scikit-image scipy
+sudo apt-get install python3-tk
 ```
 
 ### `tensorflow/models`
@@ -90,13 +91,13 @@ under the hood.
 
 ```bash
 # From tensorflow/models/research/delf/
-pip install -e . # Install "delf" package.
+pip3 install -e . # Install "delf" package.
 ```
 
 At this point, running
 
 ```bash
-python -c 'import delf'
+python3 -c 'import delf'
 ```
 
 should just return without complaints. This indicates that the DELF package is
@@ -104,18 +105,11 @@ loaded successfully.
 
 ### Troubleshooting
 
-#### Python version
+#### `pip3 install`
 
-Installation issues may happen if multiple python versions are mixed. The
-instructions above assume python2.7 version is used; if using python3.X, be sure
-to use `pip3` instead of `pip`, `python3-tk` instead of `python-tk`, and all
-should work.
-
-#### `pip install`
-
-Issues might be observed if using `pip install` with `-e` option (editable
+Issues might be observed if using `pip3 install` with `-e` option (editable
 mode). You may try out to simply remove the `-e` from the commands above. Also,
-depending on your machine setup, you might need to run the `sudo pip install`
+depending on your machine setup, you might need to run the `sudo pip3 install`
 command, that is with a `sudo` at the beginning.
 
 #### Cloning github repositories

research/delf/README.md

 # DELF: DEep Local Features
 
 [![TensorFlow 2.1](https://img.shields.io/badge/tensorflow-2.1-brightgreen)](https://github.com/tensorflow/tensorflow/releases/tag/v2.1.0)
+[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)
 
 This project presents code for extracting DELF features, which were introduced
 with the paper

research/delf/delf/python/detect_to_retrieve/DETECT_TO_RETRIEVE_INSTRUCTIONS.md

@@ -87,7 +87,7 @@ Query feature extraction can be run as follows:
 
 ```bash
 # From models/research/delf/delf/python/detect_to_retrieve
-python extract_query_features.py \
+python3 extract_query_features.py \
   --delf_config_path delf_gld_config.pbtxt \
   --dataset_file_path ~/detect_to_retrieve/data/gnd_roxford5k.mat \
   --images_dir ~/detect_to_retrieve/data/oxford5k_images \
@@ -100,7 +100,7 @@ Index feature extraction / box detection can be run as follows:
 
 ```bash
 # From models/research/delf/delf/python/detect_to_retrieve
-python extract_index_boxes_and_features.py \
+python3 extract_index_boxes_and_features.py \
   --delf_config_path delf_gld_config.pbtxt \
   --detector_model_dir parameters/d2r_frcnn_20190411 \
   --detector_thresh 0.1 \
@@ -125,7 +125,7 @@ Run query feature aggregation as follows:
 
 ```bash
 # From models/research/delf/delf/python/detect_to_retrieve
-python extract_aggregation.py \
+python3 extract_aggregation.py \
   --use_query_images True \
   --aggregation_config_path query_aggregation_config.pbtxt \
   --dataset_file_path ~/detect_to_retrieve/data/gnd_roxford5k.mat \
@@ -139,7 +139,7 @@ Run index feature aggregation as follows:
 
 ```bash
 # From models/research/delf/delf/python/detect_to_retrieve
-python extract_aggregation.py \
+python3 extract_aggregation.py \
   --aggregation_config_path index_aggregation_config.pbtxt \
   --dataset_file_path ~/detect_to_retrieve/data/gnd_roxford5k.mat \
   --features_dir ~/detect_to_retrieve/data/oxford5k_features/index_0.1 \
@@ -156,7 +156,7 @@ To run retrieval on `roxford5k`, the following command can be used:
 
 ```bash
 # From models/research/delf/delf/python/detect_to_retrieve
-python perform_retrieval.py \
+python3 perform_retrieval.py \
   --index_aggregation_config_path index_aggregation_config.pbtxt \
   --query_aggregation_config_path query_aggregation_config.pbtxt \
   --dataset_file_path ~/detect_to_retrieve/data/gnd_roxford5k.mat \
@@ -193,7 +193,7 @@ example command:
 
 ```bash
 # From models/research/delf/delf/python/detect_to_retrieve
-python perform_retrieval.py \
+python3 perform_retrieval.py \
   --index_aggregation_config_path index_aggregation_config.pbtxt \
   --query_aggregation_config_path query_aggregation_config.pbtxt \
   --dataset_file_path ~/detect_to_retrieve/data/gnd_roxford5k.mat \
@@ -215,7 +215,7 @@ K-means are not registered for GPU usage in Tensorflow.
 
 ```bash
 # From models/research/delf/delf/python/detect_to_retrieve
-python cluster_delf_features.py \
+python3 cluster_delf_features.py \
   --dataset_file_path ~/detect_to_retrieve/data/gnd_rparis6k.mat \
   --features_dir ~/detect_to_retrieve/data/paris6k_features/index_0.1 \
   --num_clusters 1024 \

research/delf/delf/python/training/README.md

@@ -13,7 +13,7 @@ Assuming the data was downloaded to `/tmp/gld_tfrecord/`, running the following
 command should start training a model:
 
 ```sh
-python tensorflow_models/research/delf/delf/python/training/train.py \
+python3 tensorflow_models/research/delf/delf/python/training/train.py \
   --train_file_pattern=/tmp/gld_tfrecord/train* \
   --validation_file_pattern=/tmp/gld_tfrecord/train* \
   --debug