Merge pull request falloutdurham#47 from MarcusFra/ch08_catfish_new

Ch8 Change catfish_server.py & add/change bash scripts

Author: falloutdurham

chapter8/catfish/catfish_server.py

@@ -1,39 +1,28 @@
-import os
 import requests
 import torch
 from flask import Flask, jsonify, request
 from io import BytesIO
 from PIL import Image
 from torchvision import transforms
-from catfish_model import CatfishModel, CatfishClasses
-from urllib.request import urlopen
-from shutil import copyfileobj
-from tempfile import NamedTemporaryFile
 
+from catfish_model import CatfishModel, CatfishClasses
 
 def load_model():
-  m = CatfishModel
-  if "CATFISH_MODEL_LOCATION" in os.environ:
-    parameter_url = os.environ["CATFISH_MODEL_LOCATION"]
-    print(f"downloading {parameter_url}")
-    with urlopen(parameter_url) as fsrc, NamedTemporaryFile() as fdst:
-      copyfileobj(fsrc, fdst)
-      m.load_state_dict(torch.load(fdst))
-      m.load_state_dict(torch.load(location))
-  return m
+    m = CatfishModel
+    m.eval()
+    return m
 
 model = load_model()
 
 img_transforms = transforms.Compose([
     transforms.Resize((224,224)),
     transforms.ToTensor(),
     transforms.Normalize(mean=[0.485, 0.456, 0.406],
-                    std=[0.229, 0.224, 0.225] )
+                         std=[0.229, 0.224, 0.225])
 ])
 
 def create_app():
     app = Flask(__name__)
-  
 
     @app.route("/")
     def status():
@@ -53,6 +42,4 @@ def predict():
         predicted_class = CatfishClasses[torch.argmax(prediction)]
         return jsonify({"image": img_url, "prediction": predicted_class})
 
-    return app
-if __name__ == '__main__':
-  app.run(host=os.environ["CATFISH_HOST"], port=os.environ["CATFISH_PORT"])
+    return app

chapter8/catfish/get-prediction.sh

@@ -0,0 +1,4 @@
+#!/bin/bash
+#run-model-service.sh
+
+curl http://127.0.0.1:8080/predict\?image_url\=https://upload.wikimedia.org/wikipedia/commons/thumb/3/36/A_domestic_shorthair_tortie-tabby_cat.jpg/412px-A_domestic_shorthair_tortie-tabby_cat.jpg

chapter8/catfish/run-flask-server.sh

@@ -0,0 +1,4 @@
+#!/usr/bin/env bash
+#run-flask-server.sh
+
+FLASK_APP=catfish_server.py FLASK_RUN_PORT=8080 flask run

chapter8/catfish/run-waitress-server.sh

@@ -0,0 +1,4 @@
+#!/usr/bin/env bash
+#run-waitress-server.sh
+
+waitress-serve --call 'catfish_server:create_app'

chapter8/catfish/Dockerfile renamed to chapter8/catfish_docker_cloud/Dockerfile

@@ -0,0 +1,9 @@
+import torch.nn as nn 
+from torchvision import models
+
+CatfishClasses = ["cat","fish"]
+
+CatfishModel = models.resnet50()
+CatfishModel.fc = nn.Sequential(nn.Linear(CatfishModel.fc.in_features,500),
+                  nn.ReLU(),
+                  nn.Dropout(), nn.Linear(500,2))

chapter8/catfish_docker_cloud/catfish_model.py

@@ -0,0 +1,57 @@
+import os
+import requests
+import torch
+from flask import Flask, jsonify, request
+from io import BytesIO
+from PIL import Image
+from shutil import copyfileobj
+from tempfile import NamedTemporaryFile
+from torchvision import transforms
+from urllib.request import urlopen
+
+from catfish_model import CatfishModel, CatfishClasses
+
+
+def load_model():
+    m = CatfishModel
+    if "CATFISH_MODEL_LOCATION" in os.environ:
+        parameter_url = os.environ["CATFISH_MODEL_LOCATION"]
+        print(f"downloading {parameter_url}")
+        with urlopen(parameter_url) as fsrc, NamedTemporaryFile() as fdst:
+            copyfileobj(fsrc, fdst)
+            m.load_state_dict(torch.load(fdst, map_location="cpu"))
+    m.eval()
+    return m
+
+
+model = load_model()
+
+img_transforms = transforms.Compose([
+    transforms.Resize((224,224)),
+    transforms.ToTensor(),
+    transforms.Normalize(mean=[0.485, 0.456, 0.406],
+                         std=[0.229, 0.224, 0.225])
+])
+
+def create_app():
+    app = Flask(__name__)
+
+    @app.route("/")
+    def status():
+        return jsonify({"status": "ok"})
+
+    @app.route("/predict", methods=['GET', 'POST'])
+    def predict():
+        if request.method == 'POST':
+            img_url = request.form.image_url
+        else:
+            img_url = request.args.get('image_url', '')
+
+        response = requests.get(img_url)
+        img = Image.open(BytesIO(response.content))
+        img_tensor = img_transforms(img).unsqueeze(0)
+        prediction =  model(img_tensor)
+        predicted_class = CatfishClasses[torch.argmax(prediction)]
+        return jsonify({"image": img_url, "prediction": predicted_class})
+
+    return app

chapter8/catfish_docker_cloud/catfish_server.py

@@ -0,0 +1,4 @@
+#!/bin/bash
+#get-prediction.sh
+
+curl http://127.0.0.1:5000/predict?image_url=https://upload.wikimedia.org/wikipedia/commons/thumb/3/36/A_domestic_shorthair_tortie-tabby_cat.jpg/412px-A_domestic_shorthair_tortie-tabby_cat.jpg

chapter8/catfish_docker_cloud/get-prediction.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+#run-docker.sh
+
+docker build -t catfish-service .
+docker run -d -p 5000:5000 --env CATFISH_MODEL_LOCATION=[URL] catfish-service:latest

chapter8/catfish_docker_cloud/run-docker.sh

@@ -2,4 +2,4 @@
 #run-model-service.sh
 
 cd /app
-waitress-serve --port ${CATFISH_PORT} --call 'catfish_server:create_app' 
+waitress-serve --port ${CATFISH_PORT} --call 'catfish_server:create_app'

chapter8/catfish/run-model-service.sh renamed to chapter8/catfish_docker_cloud/run-model-service.sh

@@ -0,0 +1,21 @@
+FROM continuumio/miniconda3:latest
+
+ARG model_parameter_file=catfishweights.pth
+ARG port=5000
+
+ENV CATFISH_PORT=$port
+ENV CATFISH_MODEL_LOCATION=/app/$model_parameter_file
+
+RUN conda install -y flask \
+  && conda install -c pytorch torchvision \
+  && conda install waitress
+RUN mkdir -p /app
+
+COPY ./catfish_model.py /app
+COPY ./catfish_server.py /app
+COPY ./$model_parameter_file /app/
+COPY ./run-model-service.sh /
+
+EXPOSE $port
+
+ENTRYPOINT ["/run-model-service.sh"]

chapter8/catfish_docker_local/Dockerfile

@@ -0,0 +1,9 @@
+import torch.nn as nn 
+from torchvision import models
+
+CatfishClasses = ["cat","fish"]
+
+CatfishModel = models.resnet50()
+CatfishModel.fc = nn.Sequential(nn.Linear(CatfishModel.fc.in_features,500),
+                  nn.ReLU(),
+                  nn.Dropout(), nn.Linear(500,2))

chapter8/catfish_docker_local/catfish_model.py

@@ -0,0 +1,50 @@
+import os
+import requests
+import torch
+from flask import Flask, jsonify, request
+from io import BytesIO
+from PIL import Image
+from torchvision import transforms
+
+from catfish_model import CatfishModel, CatfishClasses
+
+
+def load_model():
+    location = os.environ["CATFISH_MODEL_LOCATION"]
+    m = CatfishModel
+    m.load_state_dict(torch.load(location, map_location="cpu"))
+    m.eval()
+    return m
+
+
+model = load_model()
+
+img_transforms = transforms.Compose([
+    transforms.Resize((224,224)),
+    transforms.ToTensor(),
+    transforms.Normalize(mean=[0.485, 0.456, 0.406],
+                         std=[0.229, 0.224, 0.225] )
+])
+
+def create_app():
+    app = Flask(__name__)
+
+    @app.route("/")
+    def status():
+        return jsonify({"status": "ok"})
+
+    @app.route("/predict", methods=['GET', 'POST'])
+    def predict():
+        if request.method == 'POST':
+            img_url = request.form.image_url
+        else:
+            img_url = request.args.get('image_url', '')
+
+        response = requests.get(img_url)
+        img = Image.open(BytesIO(response.content))
+        img_tensor = img_transforms(img).unsqueeze(0)
+        prediction =  model(img_tensor)
+        predicted_class = CatfishClasses[torch.argmax(prediction)]
+        return jsonify({"image": img_url, "prediction": predicted_class})
+
+    return app

chapter8/catfish_docker_local/catfish_server.py

@@ -0,0 +1,4 @@
+#!/bin/bash
+#get-prediction.sh
+
+curl http://127.0.0.1:5000/predict?image_url=https://upload.wikimedia.org/wikipedia/commons/thumb/3/36/A_domestic_shorthair_tortie-tabby_cat.jpg/412px-A_domestic_shorthair_tortie-tabby_cat.jpg

chapter8/catfish_docker_local/get-prediction.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+#run-docker.sh
+
+docker build -t catfish-service .
+docker run -d -p 5000:5000  catfish-service:latest

chapter8/catfish_docker_local/run-docker.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+#run-model-service.sh
+
+cd /app
+waitress-serve --port ${CATFISH_PORT} --call 'catfish_server:create_app'