When trying to go trough https://microsoftlearning.github.io/mslearn-ai-vision/Instructions/Exercises/01-analyze-images.html from https://learn.microsoft.com/en-gb/training/modules/analyze-images/5-exercise-computer-vision

I'm getting:

Mac-Studio:image-analysis USER$ dotnet run images/street.jpg

Analyzing images/street.jpg 

The Analyze Operation under Computer Vision APIs (2023-10-01) is not supported with the current subscription key and pricing tier OpenAI.S0.
Status: 401 (Access Denied)
ErrorCode: 401

Content:
{"error":{"code":"401","message": "The Analyze Operation under Computer Vision APIs (2023-10-01) is not supported with the current subscription key and pricing tier OpenAI.S0."}}

Headers:
apim-request-id: REDACTED
Strict-Transport-Security: REDACTED
X-Content-Type-Options: REDACTED
WWW-Authenticate: AzureApiManagementKey realm="https://XXX.openai.azure.com/computervision",name="Ocp-Apim-Subscription-Key",type="header"
Date: Sun, 26 May 2024 20:40:03 GMT
Content-Length: 178
Content-Type: application/json

created AI resource Region is "East US" and Pricing tier is "Standard S0" as stated in the instruction.

Detecting faces in an Image - The Issue

For reference to the specific exercise being done, please see the following. For reference to the detect-people.py file being executed, please see:

from dotenv import load_dotenv
import os
from array import array
from PIL import Image, ImageDraw
import sys
import time
from matplotlib import pyplot as plt
import numpy as np

# import namespaces
import azure.ai.vision as sdk

def main():
    global cv_client

    try:
        # Get Configuration Settings
        load_dotenv()
        ai_endpoint = os.getenv('AI_SERVICE_ENDPOINT')
        ai_key = os.getenv('AI_SERVICE_KEY')

        # Get image
        image_file = 'images/people.jpg'
        if len(sys.argv) > 1:
            image_file = sys.argv[1]

        # Authenticate Azure AI Vision client
        cv_client = sdk.VisionServiceOptions(ai_endpoint, ai_key)
        
        # Analyze image
        AnalyzeImage(image_file, cv_client)

    except Exception as ex:
        print(ex)


def AnalyzeImage(image_file, cv_client):
    print('\nAnalyzing', image_file)

    # Specify features to be retrieved (PEOPLE)
    analysis_options = sdk.ImageAnalysisOptions()
    
    features = analysis_options.features = (
        sdk.ImageAnalysisFeature.PEOPLE
    )    

    # Get image analysis
    image = sdk.VisionSource(image_file)
        
    image_analyzer = sdk.ImageAnalyzer(cv_client, image, analysis_options)
        
    result = image_analyzer.analyze()
        
    if result.reason == sdk.ImageAnalysisResultReason.ANALYZED:
        # Get people in the image
        if result.people is not None:
            print("\nPeople in image:")
            
            # Prepare image for drawing
            image = Image.open(image_file)
            fig = plt.figure(figsize=(image.width/100, image.height/100))
            plt.axis('off')
            draw = ImageDraw.Draw(image)
            color = 'cyan'
            
            for detected_people in result.people:
                # Draw object bounding box if confidence > 50%
                if detected_people.confidence > 0.5:
                    # Draw object bounding box
                    r = detected_people.bounding_box
                    bounding_box = ((r.x, r.y), (r.x + r.w, r.y + r.h))
                    draw.rectangle(bounding_box, outline=color, width=3)
                
                    # Return the confidence of the person detected
                    print(" {} (confidence: {:.2f}%)".format(detected_people.bounding_box, detected_people.confidence * 100))
                        
            # Save annotated image
            plt.imshow(image)
            plt.tight_layout(pad=0)
            outputfile = 'detected_people.jpg'
            fig.savefig(outputfile)
            print('  Results saved in', outputfile)
        
    else:
        error_details = sdk.ImageAnalysisErrorDetails.from_result(result)
        print(" Analysis failed.")
        print("   Error reason: {}".format(error_details.reason))
        print("   Error code: {}".format(error_details.error_code))
        print("   Error message: {}".format(error_details.message))

if __name__ == "__main__":
    main()

When I execute the Python command:

python detect-people.py

or in my case:

python3 detect-people.py

I receive the following error:
module 'azure.ai.vision' has no attribute 'VisionServiceOptions'

Related to issues from the code input for Authentication of the SDK at

 # import namespaces
 import azure.ai.vision as sdk

Attempting to Diagnose the Issue

I execute detect-people.py in my zsh shell from the folder that I cloned the repository. I've gone into my file path where Python is located to locate the frame work and all I can find are the Python modules related to Azure AI 102 Modules for Analyze Images Exercise 1, which are azure.ai.vision.imageanalysis modules. I opened that configuration file and compared it to how the detect-people.py file configures authentication for Azure and I literally cannot find an azure.ai.vision module configuration file - my vision folder goes straight to a subsequent imageanalysis folder. Therefore, where my Python interpreter attempts to authenticate the SDK for access to the "VisionServiceOptions" features, it cannot. The authentication of the SDK is supposed to occur here:

# Authenticate Azure AI Vision client
cv_client = sdk.VisionServiceOptions(ai_endpoint, ai_key)

I have compared the configuration file from azure.ai.vision.imageanalysis to see if I can make something analogous to that to gain access to the 'VisionServiceOptions' features, but then I look into my actual folders and see no code for 'VisionServiceOptions', so even if I rewrote the script to pull from 'imageanalysis', I wouldn't have any 'VisionServiceOptions' features to do the face detection. I've also searched to see if the Face Detection features may be named something different so I pull something different from azure.ai.vision/sdk

Examining Correlation with an Open and Related Issue

In a previous issue that was raised, I'm unsure if the issue with installing 'azure-ai-vision' is the root of the issue. When attempting to execute pip install azure-ai-vision==0.15.1b1, I receive the following:

ERROR: Could not find a version that satisfies the requirement azure-ai-vision==0.15.1b1 (from versions: none)
ERROR: No matching distribution found for azure-ai-vision==0.15.1b1

In another raised issue that is still open (#10), I agreed, at the time, with the original poster that the solution may be to use the command:

pip install azure-ai-vision-imageanalysis

However, I believe only being able to execute this command successfully may be why I'm experiencing the problem that I'm having at the moment - I never installed the VisionServiceOptions. Please help, I have a deadline to complete my training in this within a week!

Classify images with a Azure AI Vision custom model

Create a custom model training project

Navigate to Custom models on the left, and select Train a new model. Use the following settings:

Name of model: classifyfruit
Model type: Image classification
Choose training dataset: training_images
Leave the rest as default, and select Train model

This fails immediately due to dataset corruption [p1].

[p1]

There is a piece of code that is in the laboratory that is wrong for the C# language as shown in print.

With this error, the application cannot be compiled, generating a terrible experience for the user

Exercises/01-analyze-images.html:

• Running the code on non-Windows systems (even WSL) will fail with The type initializer for 'Gdip' threw an exception.. This is the full stack trace:

  System.TypeInitializationException: The type initializer for 'Gdip' threw an exception.
   ---> System.PlatformNotSupportedException: System.Drawing.Common is not supported on non-Windows platforms. See https://aka.ms/systemdrawingnonwindows for more information.
     at System.Drawing.SafeNativeMethods.Gdip.<>c.<.cctor>b__2_0(String _, Assembly _, Nullable`1 _)
     at System.Runtime.InteropServices.NativeLibrary.LoadLibraryCallbackStub(String libraryName, Assembly assembly, Boolean hasDllImportSearchPathFlags, UInt32 dllImportSearchPathFlags)
     at System.Drawing.SafeNativeMethods.Gdip.<GdiplusStartup>g____PInvoke|32_0(IntPtr* __token_native, StartupInputEx* __input_native, StartupOutput* __output_native)
     at System.Drawing.SafeNativeMethods.Gdip.GdiplusStartup(IntPtr& token, StartupInputEx& input, StartupOutput& output)
     at System.Drawing.SafeNativeMethods.Gdip..cctor()
  

• Background removal does not accept the parameter passed to dotnet run because the URL to images/building.jpg is hard-coded.

I tried to follow this - https://github.com/MicrosoftLearning/mslearn-ai-vision/blob/main/Instructions/Exercises/01-analyze-images.md, but the namespace 'Azure.AI.Vision.Common' not resolving with Azure.AI.Vision.ImageAnalysis 1.0.0-beta.1 sdk, and hence not able to complete the exercise.
Can you please update?

The instruction needs an update to use the newer azure-ai-vision-imageanalysis library instead of azure-ai-vision (Python code).

I propose the following updates for the Python code:

Prepare to use the Azure AI Vision SDK

....
Python

```
pip install azure-ai-vision-imageanalysis
```

Detect faces in an image

Python

from dotenv import load_dotenv
import os
from PIL import Image, ImageDraw
import sys

from matplotlib import pyplot as plt

# Import namespaces
from azure.ai.vision.imageanalysis import ImageAnalysisClient
from azure.core.credentials import AzureKeyCredential
from azure.ai.vision.imageanalysis.models import VisualFeatures




def main():
    global cv_client

    try:
        # Get Configuration Settings
        load_dotenv()
        ai_endpoint = os.getenv('AI_SERVICE_ENDPOINT')
        ai_key = os.getenv('AI_SERVICE_KEY')

        # Get image
        image_file = 'images/people.jpg'
        if len(sys.argv) > 1:
            image_file = sys.argv[1]

        # Authenticate Azure AI Vision client
        cv_client = ImageAnalysisClient(ai_endpoint, AzureKeyCredential(ai_key))    
        
        # Analyze image
        AnalyzeImage(image_file, cv_client)

    except Exception as ex:
        print(ex)


def AnalyzeImage(image_file, cv_client:ImageAnalysisClient):
    print('\nAnalyzing', image_file)

    
    # Get image analysis
    with open(image_file, "rb") as f:
        image_data = f.read()

    result = cv_client.analyze(image_data=image_data, visual_features= [
        VisualFeatures.PEOPLE
    ])
        

    # Get people in the image
    if result.people is not None:
        print("\nPeople in image:")
        
        # Prepare image for drawing
        image = Image.open(image_file)
        fig = plt.figure(figsize=(image.width/100, image.height/100))
        plt.axis('off')
        draw = ImageDraw.Draw(image)
        color = 'cyan'
        
        for detected_people in result.people.list:
            # Draw object bounding box if confidence > 50%
            if detected_people.confidence > 0.5:
                # Draw object bounding box
                r = detected_people.bounding_box
                bounding_box = ((r.x, r.y), (r.x + r.width, r.y + r.height))
                draw.rectangle(bounding_box, outline=color, width=3)
            
                # Return the confidence of the person detected
                print(" {} (confidence: {:.2f}%)".format(detected_people.bounding_box, detected_people.confidence * 100))
                    
        # Save annotated image
        plt.imshow(image)
        plt.tight_layout(pad=0)
        outputfile = 'detected_people.jpg'
        fig.savefig(outputfile)
        print('  Results saved in', outputfile)
    
    else:
        print(" Analysis failed.")

if __name__ == "__main__":
    main()

The lab instructions keep referring to "Video Analyzer" although the service name is "Video Indexer". For consistency and to avoid confusion, please replace "Video Analyzer" by "Video Indexer" where appropriate.

In the last paragraph of the instructions the link is not correct, and we see a 404 page. But I'm not sure what the intention of that link is, since this exercise is mixing the terms "Video Indexer" and "Video Analyzer"

Now:
For more information about Video Analyzer, see the Video Analyzer documentation.

Should be:
For more information about Video Analyzer, see the Video Analyzer documentation.

In the Python code, the comment is written as follows:

Import namespaces

While in the instructions, both the online website instructions and the virtual lab instructions, the code is as follows:

import namespaces

In Step 2, when provisioning the resource, it should be clarified that the resource name is "Language" or "Language Service" and not "Azure AI Language Service", at least this is what the Azure Portal currently shows.

Additionally, the feature to enable custom classification is labeled under "custom features" as "Custom text classification, Custom named entity recognition, Custom summarization, Custom sentiment analysis & Custom Text Analytics for health" and there is no "asking about Additional features".