Users/rdheekonda/update read me (#61)

* Updated results location after completion of attack to be consistent with predict; fixed docker file to conform latest pip install command

* Add static Azure images to help users deploy and test Counterfit instructions in Azure Cloud

* increased memory to 12 GB, updated Counterfit jupyterlab docker images

Co-authored-by: Raja Sekhar Rao Dheekonda <rdheekonda@microsoft.com>

README.md

@@ -35,22 +35,42 @@ Choose one of these methods to get started quickly:
 
 For more information including alternative installation instructions, please visit our [wiki](https://github.com/Azure/counterfit/wiki).
 
-### Option 1: Deploy via Azure Shell
+### Option 1: Deploy and Test in Azure Cloud
 
 To run Counterfit from your browser
 
 1. Click the button below to initiate small resource deployment to your Azure account.
 
-[![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fcounterfit%2Fmaster%2Finfrastructure%2Fazuredeploy.json)
+    [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fcounterfit%2Fmaster%2Finfrastructure%2Fazuredeploy.json)
 
-2. In the configuration blade, specify your subscription and resource group.
-3. In your [Azure Shell](https://shell.azure.com), type the following, replacing `RESOURCE_GROUP` with the name of the resource group selected in the previous step.
+2. In the configuration blade, select your Subscription name, Resource group (Create new if you do not have one.), and Region from the drop-down menu as shown below.
+    
+    ![Counterfit ARM Deployment](./static/counterfit_arm_deployment.png)
 
-```
-az container exec --resource-group RESOURCE_GROUP --name counterfit --exec-command '/bin/bash'
-```
+3. The above deployment would take approximately 5-8 minutes approximately. This deployment involves creating Azure Storage Account resource for storing Counterfit generated original and adversarial images and Azure Container Instance resource for running Counterfit.
+
+4. Once deployment is successful, you can get into the Azure Container Instance using the below 2 options.
+
+    a. Using Azure Shell, click the link [Azure Shell](https://shell.azure.com) and sign-in to your Azure Subscription, type the following command in the Azure Shell terminal by replacing `RESOURCE_GROUP` with the name of the resource group selected/created in the previous ARM deployment step.
+
+    ```
+    az container exec --resource-group RESOURCE_GROUP --name counterfit --exec-command '/bin/bash'
+    ```
+
+    b. Using Azure Container Instance(ACI), follow the below steps if you would like to run Counterfit directly in the ACI instance 
+        
+    + Once deployment is successful, go to the Azure Resource Group and select `counterfit` Azure Container Instance resource as shown below.
+
+        ![Counterfit Azure Resource Group](./static/counterfit_resource_group.png)
+        ![Counterfit Azure Container Instance](./static/counterfit_container_instance.png)
+    + Once the above step is completed, it will take you to the `Container instance` page, click `Containers` under `Settings` section on the left side and click `Connect` from the menu and hit `Connect` button again.
+    
+        ![Counterfit Azure Container Instance Terminal](./static/counterfit_container_aci_terminal.png)
+
+5. Within the container terminal, launch Counterfit using the command `counterfit` in the terminal. Once Counterfit is loaded, you should be able to see a banner as shown below
+
+    ![Counterfit Terminal](./static/counterfit_terminal_cmd.PNG)
 
-4. Within the container, launch Counterfit.
 
 ### Option 2: Set up an Anaconda Python environment and install locally
 

counterfit/core/targets.py

@@ -140,8 +140,16 @@ class CFTarget:
         output = np.atleast_2d(output)
         return [self.output_classes[i] for i in np.argmax(output, axis=1)]
 
-    def get_results_folder(self, folder="results"):
-        return os.path.join(os.curdir, folder)
+    def get_results_folder(self, folder_path="counterfit/targets/results"):
+        """Folder that stores attack run results.
+
+        Args:
+            folder_path (str, optional): Defaults to "counterfit/targets/results".
+
+        Returns:
+            str: folder prefix path where attack results would be stored.
+        """
+        return folder_path
 
     def get_data_type_obj(self):
         target_data_types = {

counterfit/reporting/image.py

@@ -1,17 +1,17 @@
-import numpy as np
 import hashlib
 
-from counterfit.core.reporting import CFReportGenerator
-from counterfit.data.image import ImageDataType
-from PIL import Image
-from rich.table import Table
+import numpy as np
 from azure.storage.blob import BlobClient, ContentSettings
 from counterfit.core.output import CFPrint
+from counterfit.core.reporting import CFReportGenerator
 from counterfit.core.utils import (get_azure_storage_sas_uri,
                                    get_image_in_bytes, get_mime_type,
                                    get_predict_folder,
                                    is_img_save_in_azure_storage,
                                    transform_numpy_to_bytes)
+from counterfit.data.image import ImageDataType
+from PIL import Image
+from rich.table import Table
 
 
 class ImageReportGenerator(CFReportGenerator):
@@ -199,4 +199,4 @@ class ImageReportGenerator(CFReportGenerator):
             str(d)
         )
 
-        CFPrint.output(table)
+        CFPrint.output(table)

infrastructure/Dockerfile

@@ -11,14 +11,10 @@ RUN apt-get update \
 
 WORKDIR /home/counterfituser
 
-COPY requirements.txt .
-
-RUN pip install --no-cache-dir -r requirements.txt
-RUN pip install tensorflow python-Levenshtein
-
-
 COPY . .
 
+RUN pip install .[dev]
+
 RUN chown -R counterfituser:counterfituser /home/counterfituser
 USER counterfituser
 

infrastructure/DockerfileCounterfitJupyterlab.dockerfile

@@ -11,7 +11,7 @@ RUN apt-get update \
 USER 1000
 RUN git clone https://github.com/Azure/counterfit.git \
    && cd counterfit \
-   && pip install --no-cache-dir -r requirements.txt\
+   && pip install .[dev]\
    && cd ..
 EXPOSE 8888
 EXPOSE 2718

infrastructure/DockerfileJupyterhubShell.dockerfile

@@ -10,6 +10,7 @@ RUN apt-get update \
     && rm -rf /var/lib/apt/lists/* \
     && sed -i "s/\"default\": \"inherit\"/\"default\": \"dark\"/g" /opt/conda/share/jupyter/lab/schemas/@jupyterlab/terminal-extension/plugin.json
 USER 1000
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+COPY . .
+
+RUN pip install .[dev]
 EXPOSE 8888

infrastructure/azuredeploy.json

@@ -60,7 +60,7 @@
     },
     "memoryInGb": {
       "type": "string",
-      "defaultValue": "6.0",
+      "defaultValue": "12.0",
       "metadata": {
         "description": "The amount of memory to allocate to the container in gigabytes."
       }