From 4e1c93fc4bc383ecfa714f566ea7583a7321351e Mon Sep 17 00:00:00 2001
From: Jamey Calabrese <jamey.calabrese@uconn.edu>
Date: Tue, 30 Mar 2021 00:56:23 -0400
Subject: [PATCH] Created a script which is rough around the edges to check for
 work, classify an image against a model, and post the result back to the data
 service

---
 .gitignore       |  4 ++-
 requirements.txt | 11 +++++++
 src/__init__.py  | 84 ++++++++++++++++++++++++++++++++++++++++++++++++
 3 files changed, 98 insertions(+), 1 deletion(-)
 create mode 100644 src/__init__.py

diff --git a/.gitignore b/.gitignore
index 82adb58..de75073 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,4 @@
 __pycache__
-venv
+env
+.ipynb_checkpoints
+.vscode
diff --git a/requirements.txt b/requirements.txt
index 7763fb4..4c15161 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -3,6 +3,8 @@ astunparse==1.6.3
 cachetools==4.1.1
 certifi==2020.6.20
 chardet==3.0.4
+cycler==0.10.0
+decorator==4.4.2
 gast==0.3.3
 google-auth==1.22.1
 google-auth-oauthlib==0.4.1
@@ -10,22 +12,30 @@ google-pasta==0.2.0
 grpcio==1.33.1
 h5py==2.10.0
 idna==2.10
+imageio==2.9.0
 Keras==2.4.3
 Keras-Preprocessing==1.1.2
+kiwisolver==1.3.1
 Markdown==3.3.2
+matplotlib==3.4.0
+networkx==2.5
 numpy==1.18.5
 oauthlib==3.1.0
 opt-einsum==3.3.0
 pandas==1.1.3
+Pillow==8.1.2
 protobuf==3.13.0
 pyasn1==0.4.8
 pyasn1-modules==0.2.8
+pyparsing==2.4.7
 python-dateutil==2.8.1
 pytz==2020.1
+PyWavelets==1.1.1
 PyYAML==5.3.1
 requests==2.24.0
 requests-oauthlib==1.3.0
 rsa==4.6
+scikit-image==0.18.1
 scipy==1.5.3
 six==1.15.0
 tensorboard==2.3.0
@@ -33,6 +43,7 @@ tensorboard-plugin-wit==1.7.0
 tensorflow==2.3.1
 tensorflow-estimator==2.3.0
 termcolor==1.1.0
+tifffile==2021.3.17
 urllib3==1.25.11
 Werkzeug==1.0.1
 wrapt==1.12.1
diff --git a/src/__init__.py b/src/__init__.py
new file mode 100644
index 0000000..7ef36a1
--- /dev/null
+++ b/src/__init__.py
@@ -0,0 +1,84 @@
+import os
+import keras
+import numpy
+import requests
+import sys
+import tensorflow
+import time
+
+from PIL import Image
+from skimage import transform
+from io import BytesIO
+
+def worker_loop(hostname, model):
+    # First step: Check for work from the data service
+    work_check = requests.post(hostname + "/requestwork")
+    work_check = work_check.json()
+    classification_id = work_check['classification_id']
+
+    # This is the do nothing and wait case.
+    if classification_id == None:
+        return False
+
+    # If we've been assigned work we move onto step 2
+
+    # Get the image assigned to the classification request
+    image_response = requests.get(hostname + "/getimage?classification_id={}".format(classification_id))
+    image = Image.open(BytesIO(image_response.content))
+    image = numpy.array(image).astype('float32')/255
+    image = transform.resize(image, (218, 178, 3)) # TODO - parameterize this image resize
+    image = numpy.expand_dims(image, axis=0)
+
+    # Make a prediction on the image using the model
+    pred = model.predict(image)[0, 0]
+
+    # Post the prediction back to the data service
+    response_dict = dict()
+    response_dict['classification_id'] = classification_id
+    response_dict['assigned_on'] = work_check['assigned_on']
+    response_dict['errors'] = "" # TODO - Figure out where keras will spit out errors
+
+    # Using the result of the prediction assing a classification
+    # TODO - In the future these possibilities should be fetchable from the data service
+    if round(pred) == 1:
+        response_dict['classification'] = "covid-19"
+    else:
+        response_dict['classification'] = "not covid-19"
+
+    # Report the predicted classification back to the data service
+    requests.post(hostname + "/reportclassification", json=response_dict)
+
+    # Return true to denote that there was previously work assigned to the worker instance
+    # and there may still be more images to classify
+    return True
+
+if __name__ == "__main__":
+    arguments = sys.argv[1:] # ignore __init__.py argument
+    argc = len(arguments)
+
+    hostname = "http://127.0.0.1:8000"
+    model = "../covid_fine_tuned.h5"
+    interval = 15.0
+
+    for i in range(0,len(arguments),2):
+        parameter = arguments[i]
+        if i+1 >= len(arguments):
+            raise Exception("No value passed for parameter {}", parameter)
+
+        value = arguments[i+1]
+        
+        if parameter == "--hostname":
+            hostname = value
+        elif parameter == "--model":
+            model = value
+        elif parameter == "--retry_interval":
+            interval = float(value)
+
+    model = keras.models.load_model(model)
+
+    # The loop of the worker instance
+    while True:
+        work_check = worker_loop(hostname, model)
+        if not work_check:
+            time.sleep(interval)
+