diff --git a/README.md b/README.md index e88b44c..68f0693 100644 --- a/README.md +++ b/README.md @@ -145,7 +145,7 @@ The web app will start running on `http://127.0.0.1:5000/`. Open this URL in you Here is what it looks like:

- Flask Web App + Flask Web App

Note that the app has also been deployed to Heroku [at this link](https://ai-multipurpose-classifier-b1655f2a20d4.herokuapp.com/). However, due to changes in Heroku's free tier regarding available Dynos (and I'm a broke college student), the app may not work as expected. If you encounter any issues, please run the app locally using the instructions above. @@ -207,7 +207,7 @@ The output video will display the detected vehicles along with their class label Example output:

- Vehicle Classification Output + Vehicle Classification Output

--- @@ -258,7 +258,7 @@ The output will be a video displaying the detected faces along with their estima Example output:

- Face Classification Output + Face Classification Output

--- @@ -301,7 +301,7 @@ The output will be displayed the detected mood in the image, video, or webcam st Example output:

- Mood Classification Output + Mood Classification Output

--- @@ -362,7 +362,7 @@ The output will display the class labels of the characters detected in the image Example output:

- Character Classification Output + Character Classification Output

--- @@ -405,7 +405,7 @@ The output will display the class label of the flower detected in the image alon Example output: Here are the sample image of Daisy flowers.

- Flower Classification Output + Flower Classification Output

--- @@ -451,7 +451,7 @@ The output will display the class labels of the objects detected in the image al Example output:

- Object Classification Output + Object Classification Output

--- @@ -493,7 +493,7 @@ The output will display the class labels of the animals detected in the image al Example output:

- Animal Classification Output + Animal Classification Output

--- @@ -533,7 +533,7 @@ You will see the output of the speech recognition process in the console. The sc Example output:

- Speech Recognition Output + Speech Recognition Output

--- @@ -617,13 +617,13 @@ The output will display the sentiment classification of the input sentence. The **Training Output Example:**

- Sentiment Classifier Training Output + Sentiment Classifier Training Output

**Classification Output Example:**

- Sentiment Classifier Classification Output + Sentiment Classifier Classification Output

Feel free to experiment with the sentiment classifier and test it with your own sentences and explore how powerful sentiment analysis can be! @@ -665,7 +665,7 @@ For any questions or issues, please refer to the contact information below: ## License -This project is licensed under the MIT License - see the [LICENSE](../LICENSE) file for details. +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. ## Live Information Website