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Grad-CAM explanation in the classification inference UI #178

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46 changes: 36 additions & 10 deletions server/deep_learning.R
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Original file line number Diff line number Diff line change
Expand Up @@ -870,17 +870,34 @@ deep_learning = function() {

observeEvent(input$start_img_class_inference, {
req(input$infer_img_class_upload, input$infer_img_class_checkpoint_dropdown)
img_class_inference_result(list(status = "Running...", prediction = "Processing...", error = NULL))
img_class_inference_result(list(status = "Running...", prediction = "Processing...", error = NULL, image_url = NULL))
tryCatch({
req <- dl_request("/inference/image-classification") %>%
req_body_multipart(
image = curl::form_file(input$infer_img_class_upload$datapath),
model_checkpoint = input$infer_img_class_checkpoint_dropdown
)
resp_data <- resp_body_json(req_perform(req))
img_class_inference_result(list(status = "Success", prediction = resp_data$prediction, error = NULL))
if (isTRUE(input$infer_img_class_explain)) {
# Grad-CAM: returns prediction, confidence, and a heatmap URL.
req <- dl_request("/explain/image-classification") %>%
req_body_multipart(
image = curl::form_file(input$infer_img_class_upload$datapath),
model_checkpoint = input$infer_img_class_checkpoint_dropdown
)
resp_data <- resp_body_json(req_perform(req))
pred_text <- resp_data$prediction
if (!is.null(resp_data$confidence)) {
pred_text <- sprintf("%s (confidence: %.1f%%)", pred_text, 100 * as.numeric(resp_data$confidence))
}
img_class_inference_result(list(status = "Success", prediction = pred_text,
error = NULL, image_url = resp_data$output_url))
} else {
req <- dl_request("/inference/image-classification") %>%
req_body_multipart(
image = curl::form_file(input$infer_img_class_upload$datapath),
model_checkpoint = input$infer_img_class_checkpoint_dropdown
)
resp_data <- resp_body_json(req_perform(req))
img_class_inference_result(list(status = "Success", prediction = resp_data$prediction,
error = NULL, image_url = NULL))
}
}, error = function(e) {
img_class_inference_result(list(status = "Error", prediction = NULL, error = as.character(e)))
img_class_inference_result(list(status = "Error", prediction = NULL, error = as.character(e), image_url = NULL))
})
})

Expand Down Expand Up @@ -930,7 +947,16 @@ deep_learning = function() {
output$img_class_prediction_output <- renderText({
img_class_inference_result()$prediction
})

# Grad-CAM heatmap overlay (only populated when "Explain" was requested).
output$img_class_explain_output <- renderImage({
res <- img_class_inference_result()
req(res$status == "Success", res$image_url)
image_url <- paste0(api_url, res$image_url)
temp_file <- tempfile(fileext = ".png")
download.file(image_url, temp_file, mode = "wb")
list(src = temp_file, contentType = 'image/png', alt = "Grad-CAM heatmap")
}, deleteFile = TRUE)

output$seg_inference_status_ui <- renderUI({
res <- seg_inference_result()
if (res$status == "Running...") {
Expand Down
7 changes: 7 additions & 0 deletions ui/deeplearning_ui.R
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Original file line number Diff line number Diff line change
Expand Up @@ -359,6 +359,7 @@ deeplearning_ui = function() {
textInput("infer_img_class_run_name", "Enter Run Name to Find Checkpoints", ""),
selectInput("infer_img_class_checkpoint_dropdown", "Select Checkpoint", choices = NULL),
fileInput("infer_img_class_upload", "Upload Image for Classification"),
checkboxInput("infer_img_class_explain", "Explain prediction (Grad-CAM heatmap)", value = FALSE),
actionButton("start_img_class_inference", "Run Inference", class = "btn-info", style="margin-top: 10px;")
),
hr(),
Expand All @@ -367,6 +368,12 @@ deeplearning_ui = function() {
div(
style = "background-color: #f8f9fa; border: 1px solid #dee2e6; border-radius: 5px; padding: 15px; margin-top: 5px; min-height: 50px; font-size: 1.1em;",
textOutput("img_class_prediction_output")
),
conditionalPanel(
condition = "input.infer_img_class_explain == true",
h5("Why? Grad-CAM heatmap", style = "margin-top: 15px;"),
helpText("Warmer regions contributed more to the predicted class."),
imageOutput("img_class_explain_output", height = "auto")
)
),

Expand Down