@The Class of AI Thank you for the video. The dataset I am currently using has no test.csv. How do I generate my test.csv such that I can use it to test the model. Or do I do that manually. I have the test folder that contains the all the images I want to use to test. Thank you.
@prashilramteke5622 Жыл бұрын
thank you so much sir this is very good explanation, but i question sir can this model will classify only one image? and it should give me class of that image?
@TheClassofAI9 ай бұрын
You can classify each at a time and pass them as a batch, totally upto you!
@turbophilable2 жыл бұрын
Thanks sir i hv been searching for this for quite some time now..most helpful
@TheClassofAI2 жыл бұрын
You are most welcome Philip
@neelabhsomani51292 жыл бұрын
Amazing video! Just had a small doubt. How did you make the csv file of your labels?
@TheClassofAI2 жыл бұрын
Dear Neelabh, I have downloaded the data from Kaggle and labels are already stored in the CSV file. Hope this helps.
@joker2ify2 жыл бұрын
Great video! Just a quick question, how do you print the images in the train or validation folders?
@TheClassofAI2 жыл бұрын
Please share the screenshot of where and what you are trying to print.
@shahafraz32008 ай бұрын
Hi. Can you plz guide me how to create this test.csv file
@TheClassofAI8 ай бұрын
Your submissions usually have two columns: an ID column and a prediction column. The ID field comes from the test data (keeping whatever name the ID field had in that data, which for the housing data is the string 'Id'). The prediction column will use the name of the target field. We will create a DataFrame with this data, and then use the dataframe's to_csv method to write our submission file. Explicitly include the argument index=False to prevent pandas from adding another column in our CSV file.
@chintanparmar75333 жыл бұрын
Thanks for video!! There was a step to check the number of images across classes(cloudy, fog etc)...is it required to be balanced across classes to get better accuracy?
@TheClassofAI3 жыл бұрын
Yes, we can use resampling to balance the classes. Otherwise, better to use Sensitivity-Specificity Metrics and use a confusion matrix to see the performance.
@chintanparmar75333 жыл бұрын
Given a training dataset which has pdf having scan image of restaurant invoice...need code for nlp model to extract subtotal from receipts...any such sample code available?
@TheClassofAI3 жыл бұрын
I believe the only way to do it is by using Optical Character Recognition (OCR). Use OCR to read the number/total and then learn it.
@ibrahimsincap37052 жыл бұрын
How can I use my own dataset for this?
@indointanchannel Жыл бұрын
Amazing video. Thank you so much for your content. it is advantageous. it solved my problem of splitting datasets in folder management.
@TheClassofAI Жыл бұрын
Glad it helped! Keep learning :-)
@AghaKhan93 жыл бұрын
One of the best videos and solved my problem... Thank you so much sir ❤️
@TheClassofAI2 жыл бұрын
Most welcome
@ayushpratap63112 жыл бұрын
Sir , i am getting error in CCN model section, My epochs are not running and giving the erroe as : InvalidArgumentError: logits and labels must be broadcastable: logits_size=[16,5] labels_size=[16,4] [[node categorical_crossentropy/softmax_cross_entropy_with_logits (defined at /usr/local/lib/python3.7/dist-packages/keras/backend.py:5010) ]] [Op:__inference_train_function_3283] plese solve the issue
@TheClassofAI2 жыл бұрын
Can you please retry or share the screenshot?
@IntanMire Жыл бұрын
sir, How do split dataset if we have 3 splits(train, valid, and test). I have an error like below. split_size = .85 split_data(YES_SOURCE_DIR, TRAINING_YES_DIR, VALID_YES_DIR, TEST_YES_DIR, split_size) split_data(NO_SOURCE_DIR, TRAINING_NO_DIR, VALID_NO_DIR, TEST_NO_DIR, split_size) TypeError: split_data() takes 4 positional arguments but 5 were given Please you give a problem solver about this. Thank you so much. Greeting.
@TheClassofAI Жыл бұрын
Can you please share the screenshot of the error to theclassoai@gmail. com
@sheetalnagar3882 Жыл бұрын
Very Nice video. Can you guide me how to find RECALL value for MULTICLASS IMAGE CLASSIFICATION in keras?
@TheClassofAI Жыл бұрын
Please try this code: def macro_recall(y_true, y_pred): # find the number of classes num_classes = len(np.unique(y_true)) # initialize recall to 0 recall = 0 # loop over all classes for class_ in list(y_true.unique()): # all classes except current are considered negative temp_true = [1 if p == class_ else 0 for p in y_true] temp_pred = [1 if p == class_ else 0 for p in y_pred] # compute true positive for current class tp = true_positive(temp_true, temp_pred) # compute false negative for current class fn = false_negative(temp_true, temp_pred) # compute recall for current class temp_recall = tp / (tp + fn + 1e-6) # keep adding recall for all classes recall += temp_recall # calculate and return average recall over all classes recall /= num_classes return recall
@jaswanthchowdary37002 жыл бұрын
can u tell the model name u have used in this?
@TheClassofAI2 жыл бұрын
Hi Jaswanth, it is a simple CNN model with Data Augmentation. I have not used any transfer learning or pre-trained model for this multi-class classification. If you have any further queries, please get in touch. Thank you!
@abhijeetkumar80702 жыл бұрын
Kindly help me with this error, i'm a complete newbie trying to apply this process to another model. InvalidArgumentError for model.fit_generator (deprecated)
@TheClassofAI2 жыл бұрын
Model.fit_generator is deprecated starting from TensorFlow 2.1.0 which is currently in rc1. You can find the documentation for tf-2.1.0-rc1 here: www.tensorflow.org/versions/r2.1/api_docs/python/tf/keras/Model#fit
@whatsmyname8778 Жыл бұрын
Did you ever fix the problem?
@ghulammustafa012 жыл бұрын
what is inside the test.csv file
@TheClassofAI2 жыл бұрын
Hi Ghulam, it has ground truth or you can say true values of the test dataset. In my code, please see cell 33, where I have used it. If you have any further doubts, please get in touch. Thank you!
@akinboyeyusuff2152 жыл бұрын
@@TheClassofAI Thank you for the video. The dataset I am currently using has no test.csv. How do I generate my test.csv such that I can use it to test the model. Or do I do that manually. Thank you.
@moisesdesouzafeitosa33643 жыл бұрын
Congrats and thank you for the video.
@TheClassofAI3 жыл бұрын
You are most welcome. Thank you for watching.
@eranfeit2 жыл бұрын
Thanks for this video
@TheClassofAI2 жыл бұрын
Most welcome
@anthonymipawa88303 жыл бұрын
Very informative video, thank you
@TheClassofAI3 жыл бұрын
Many thanks!
@beda42092 жыл бұрын
Thank you for the video! I have the problem though, that the prediction comes out as integers, meaning it predicts like so [0 0 1 0]. I would like it to give me floats like [0.5 0.7 0.1 0.5] for example
@TheClassofAI2 жыл бұрын
In line 32: Please don't use "argmax" because it returns the indices of the maximum values along an axis. Try this code when predicting test dataset array = model.predict(test_preprocessed_images, batch_size=1, verbose=1) print(array)
@poraspatle7980 Жыл бұрын
Is it possible to create multi-class image classification and captioning without using Tensorflow, Keras, or sklearn
@TheClassofAI Жыл бұрын
Yes, it is possible.
@poraspatle7980 Жыл бұрын
@@TheClassofAI can you give a outline for this ?
@TheClassofAI Жыл бұрын
@@poraspatle7980 I think this blog can help you medium.com/analytics-vidhya/how-to-build-a-multi-class-image-classification-model-without-cnns-in-python-660f0f411764
@chintanparmar75333 жыл бұрын
In general how to improve accuracy?
@TheClassofAI3 жыл бұрын
You can use different transfer learning methods for domain adaptation.
@anujanaphade45493 жыл бұрын
How to split dataset in train and test set?
@TheClassofAI3 жыл бұрын
Anuja: As I did in cell 9 of the jupyter notebook for train and validation. You can use the same to create a test set.
@anilkumarchannamsettti2 жыл бұрын
Very informative video Thank you so much sir
@TheClassofAI2 жыл бұрын
Thank you, Anil :-) Keep Watching
@anilkumarchannamsettti2 жыл бұрын
Based on your code I have an error due to split data there is no such file directory
@anilkumarchannamsettti2 жыл бұрын
[Errno 2] No such file or directory: '/content/dataset/cloudycloudy47.jpg'
@anilkumarchannamsettti2 жыл бұрын
I got it my directory name changes
@TheClassofAI2 жыл бұрын
Thank you for raising the query. Glad to know that you have sorted it.
@chintanparmar75333 жыл бұрын
Is this code on github?
@TheClassofAI3 жыл бұрын
@Chintan: Kindly see the link to GitHub: github.com/theclassofai/Multiclass_Image_Classification
@anilkumarchannamsettti2 жыл бұрын
weather dataset is free
@TheClassofAI2 жыл бұрын
Yes it is free. You only need Kaggle account to download the data
@umerzamankhan45362 жыл бұрын
Sir , i am getting error in CCN model section, My epochs is not running and giving the erroe as : InvalidArgumentError: logits and labels must be broadcastable: logits_size=[16,5] labels_size=[16,22] [[node categorical_crossentropy/softmax_cross_entropy_with_logits (defined at /usr/local/lib/python3.7/dist-packages/keras/backend.py:5010) ]] [Op:__inference_train_function_3283 please help! sir
@TheClassofAI2 жыл бұрын
Can you please send me the screenshots or share the notebook with me theclassofai@gmail.com ? Thank you!
@nasroayed30652 жыл бұрын
@@TheClassofAI i have the same error
@nasroayed30652 жыл бұрын
did u found a solution ?? @Umer Zaman Khan
@umerzamankhan45362 жыл бұрын
@@nasroayed3065 yes bro
@nasroayed30652 жыл бұрын
@@umerzamankhan4536 can u help me plz ? how did u fix the probleme ?