static Appraisal CreateAppraisal(Bitmap sourceImage, ComputerVisionService.AnalysisBlob analysisResult)
{
Caption caption = GetCaption(analysisResult.generalAnalysisResult);
Console.WriteLine("Caption: " + caption.Text + " " + caption.Confidence);
string foregroundColor = GetForegroundColor(analysisResult.generalAnalysisResult);
float confidence = (float)caption.Confidence;
bool isOld = IsOld(analysisResult.generalAnalysisResult);
float expensiveMultiplier = GetPriceExpensiveMultiplier(analysisResult.generalAnalysisResult);
Console.WriteLine("Is Old: " + isOld);
bool isBlackAndWhite = IsBlackAndWhite(analysisResult.generalAnalysisResult);
Console.WriteLine("Is Black and White: " + isBlackAndWhite);
bool isPainting = PaintingDetection.IsPainting(analysisResult);
Console.WriteLine("Is Painting: " + isPainting);
bool isPhoto = !isPainting && IsPhoto(analysisResult.generalAnalysisResult);
Console.WriteLine("Is Photo: " + isPhoto);
bool isSign = SignDetection.IsSign(analysisResult);
Console.WriteLine("Is Sign: " + isSign);
int?extractedYear = YearExtractor.ExtractYear(analysisResult.ocrAnalysisResult);
Description.Arguments descriptionArguments = new Description.Arguments
{
foregroundColor = foregroundColor,
isOld = isOld,
isBlackAndWhite = isBlackAndWhite,
isPainting = isPainting,
isPhoto = isPhoto,
isSign = isSign,
};
string descriptionText = Description.Get(caption, descriptionArguments);
Console.WriteLine("Final Description Text: " + descriptionText);
Console.WriteLine("Extracted Year: " + extractedYear);
string extractedLocale = LanguageCodeToLocation.LookUp(analysisResult.ocrAnalysisResult);
Console.WriteLine("Extracted Locale: " + extractedLocale);
Random random = GetDeterministicRandom(sourceImage);
Bitmap composedImage = ComposeImage(sourceImage, descriptionText, confidence, isOld, isBlackAndWhite && isPhoto, expensiveMultiplier, isPainting, isSign, extractedYear, extractedLocale, random);
return(new Appraisal {
image = composedImage, comment = descriptionText
});
}
public static float GetSignConfidence(ComputerVisionService.AnalysisBlob analysisResult)
{
float cumulativeConfidence = 0.0f;
// if an image has any of these tags it's more likely to be a sign
string[] signTags =
{
"text",
"sign",
"book",
};
foreach (string tag in signTags)
{
if (analysisResult.generalAnalysisResult.Description.Tags.Contains(tag))
{
cumulativeConfidence += 0.5f;
}
}
string[] signDescriptions =
{
"text",
"sign",
"book",
"piece of paper",
};
if (analysisResult.generalAnalysisResult.Description.Captions.Count() != 0)
{
foreach (string description in signDescriptions)
{
if (analysisResult.generalAnalysisResult.Description.Captions[0].Text.Contains(description))
{
cumulativeConfidence += 0.5f;
}
}
}
Console.WriteLine("Sign confidence: " + cumulativeConfidence);
return(cumulativeConfidence);
}
public static bool IsPainting(ComputerVisionService.AnalysisBlob analysisResult)
{
return(GetPaintingConfidence(analysisResult) >= 0.5f);
}
public static float GetPaintingConfidence(ComputerVisionService.AnalysisBlob analysisResult)
{
if (analysisResult.generalAnalysisResult.IsClipArt() ||
analysisResult.generalAnalysisResult.IsLineDrawing())
{
return(0.0f);
}
if (analysisResult.generalAnalysisResult.IsBlackAndWhite())
{
return(0.0f);
}
float cumulativeConfidence = 0.0f;
// if an image has any of these tags it's more likely to be a painting
string[] paintingTags =
{
"view",
"outdoor",
"indoor",
"mountain",
"hill",
"grass",
"posing",
"photo",
"painting",
"person",
"man",
"woman",
"girl",
"boy",
"mirror",
"people",
"group",
"clouds",
"sitting",
"river",
"tree",
"lake",
};
foreach (string tag in paintingTags)
{
if (analysisResult.generalAnalysisResult.Description.Tags.Contains(tag))
{
cumulativeConfidence += 0.1f;
}
}
// if an image has any of these tags it's less likely to be a painting
string[] notPaintingTags =
{
"stone",
"wooden",
"sign",
"window",
};
foreach (string tag in notPaintingTags)
{
if (analysisResult.generalAnalysisResult.Description.Tags.Contains(tag))
{
cumulativeConfidence -= 0.1f;
}
}
string[] paintingDescriptions =
{
"standing in a room",
"posing for the camera",
"looking at the camera",
"a view of",
"a close up of a person",
"painting",
"in front of a mirror",
"a group of people",
};
if (analysisResult.generalAnalysisResult.Description.Captions.Count() != 0)
{
foreach (string description in paintingDescriptions)
{
if (analysisResult.generalAnalysisResult.Description.Captions[0].Text.Contains(description))
{
cumulativeConfidence += 0.4f;
}
}
}
Console.WriteLine("Painting confidence: " + cumulativeConfidence);
return(cumulativeConfidence);
}
static void CreateAppraisals(PostToTwitterMode postToTwitterMode, int numberOfAppraisals)
{
Console.WriteLine("Getting collection listing");
Art art = new Art(new IArtSource[] { new HarvardArtMuseum(), new MetropolitanMuseumOfArt() });
IEnumerable <Art.Object> responseObjects = art.GetRandomObjects(numberOfAppraisals);
Console.WriteLine("Found " + responseObjects.Count() + " results");
int objectCounter = 0;
foreach (Art.Object responseObject in responseObjects)
{
Console.WriteLine("-----------------------------------------------------------------------");
string imageUrl = responseObject.imageURL;
Console.WriteLine("image url: " + imageUrl);
string fullListingURL = responseObject.listingURL;
Console.WriteLine("Listing page: " + fullListingURL);
Bitmap originalImage = Web.DownloadImage(imageUrl);
if (originalImage != null)
{
Bitmap resizedImage = ImageTransforms.ResizeToWithinAnalysisLimits(originalImage);
if (Directory.Exists("images"))
{
string originalDestinationFilePath = @"images/sourceImage" + objectCounter + ".jpg";
originalImage.Save(originalDestinationFilePath);
string resizedDestinationFilePath = @"images/resizedImage" + objectCounter + ".jpg";
resizedImage.Save(resizedDestinationFilePath);
}
ComputerVisionService.AnalysisBlob analysisBlob = ComputerVisionService.GetAnalysisBlob(resizedImage);
string tagString = "";
foreach (string tag in analysisBlob.generalAnalysisResult.Description.Tags)
{
tagString += tag + ", ";
}
Console.WriteLine("Tags: " + tagString);
string accentColor = ColorTable.GetClosestColorName(analysisBlob.generalAnalysisResult.Color.AccentColor);
Console.WriteLine("Foreground: " + analysisBlob.generalAnalysisResult.Color.DominantColorForeground + " Background: " + analysisBlob.generalAnalysisResult.Color.DominantColorBackground + " Accent: " + accentColor);
if (analysisBlob.generalAnalysisResult.Categories != null)
{
string categoryString = "";
foreach (Category category in analysisBlob.generalAnalysisResult.Categories)
{
categoryString += category.Name + ", ";
}
Console.WriteLine("Categories: " + categoryString);
}
Appraisal appraisal = CreateAppraisal(originalImage, analysisBlob);
string tweetableText = GetTweetableText(appraisal.comment, responseObject.listingURL, responseObject.artSourceHashTag);
if (Directory.Exists("images"))
{
string destinationFilePath = @"images/finalImage" + objectCounter + ".jpg";
appraisal.image.Save(destinationFilePath);
using (StreamWriter file = File.CreateText(@"images/comment" + objectCounter + ".txt"))
{
file.WriteLine(tweetableText);
}
}
if (postToTwitterMode == PostToTwitterMode.Yes)
{
TweetAppraisal(appraisal.image, tweetableText);
}
}
objectCounter++;
}
}
public static bool IsSign(ComputerVisionService.AnalysisBlob analysisResult)
{
return(GetSignConfidence(analysisResult) >= 0.5f);
}
