FINAL PRESENTATION + POSTER
Slide 7 source links: 1. Diagram 2. Diagrams 3. Book Slide 25: 1. GitHub 2. Blog 3. Flowcharts Digital Takeaway: 1. Robot Inspiration
DAY 1: FLOWCHART + JIRA
New JIRA Tickets I opened: I created to summarize the findings of my internship regarding steps to process and classify images with HPCC GNN. In the future, anyone wishing to use their own images to train the GNN model can refer to this.
DAY 3+4: TESTING VARIOUS THOR SLAVES
With the MobileNetV2 model, 224x224x3 images, and 5 epochs, I ran various number of thor slaves with default CPU and memory to evaluate differences in accuracy and timing. # of Thor Slaves (with default CPU and Memory) End Time (Total Cluster Time) 1 *error-terminated 2 *error-terminated 4 (default # of thor slaves) 28:12 Second trial:28:13…
DAY 1: README.MD
As I continued working with the HPCC GNN model, I began creating a README.md file to document the steps so that later on, I could turn it into “instructions” for someone to recreate my project. So far, the README.md file outlines how to setup Kubernetes, use AKS created by others, complete the Azure storage setup,…
DAY 1: TESTING DIFFERENT MODELS
Dataset size: 4839 images I changed the model name in Jupyter Notebook to popular image classification models. List of models: https://keras.io/api/applications/ MobileNetV2 Between 37 and 48 seconds per epoch Reached 100% accuracy on the first epoch InceptionResNetV2 This model link didn’t work: So, I tested a different link for the same model and it worked…
WEEKEND + DAY 1: OPENING JIRAS
JIRA: HPCC-26359 Create storage account secret error on Mac After trying to run the create-secret.sh file with the command ./create-secret.sh, an error came up saying “exactly one NAME is required, got 2”. JIRA: ML-496 While experimenting with different models to see how changing the model affects the accuracy/time taken, I got this error message for…
DAY 5 + WEEKEND: PLAN
Confirm that the dataset size is 4,839 images Run the full dataset with different models in Jupyter Notebook MobileNetV2 InceptionResNetV2 NASNetMobile EfficientNet_V2 bit Run GPU on the desktop On the HPCC GNN model, change the number of thor slaves (1, 2, 4, 8, 12, 20) and document how this variable affects the total cluster time…
DAY 4+5: JIRA SOLUTION
Following Lili and Roger’s advice, I changed the code from UNSIGNED1 (which is 1 byte) to UNSIGNED4 (4 bytes). Previously, the maximum was 255 images before the model wouldn’t run anymore. Today, I tested 256 images and it successfully worked. The next step was to spray all 4,000+ images and run the model with the…
DAY 2+3: GNN MODEL
The main priority this week has been communicating with other LexisNexis employees to fix the GNN Model 255 images constraint. As of right now, we are examining issues in the code itself rather than Azure/the cloud. While working on that, I have also been testing different models (besides the TensorFlow Transfer Learning one) to see…
DAY 5: CONDENSED MODEL
Based on the TensorFlow Transfer Learning Model, I created a condensed version that is shorter, but fits the same purpose. Since the first time I used this model, the accuracy has always reached 100% after the first epoch. I was curious as to what would happen if I added a new image with a different…
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