Added checkbox for EigenCAM

app.py

@@ -64,7 +64,7 @@ def display_false_detection_data(false_detection_data, number_of_samples):
 
     return fig
 
-def inference(input_img, conf_thres, iou_thres, is_false_detection_images=True, num_false_detection_images=10):
+def inference(input_img, conf_thres, iou_thres, is_eigen_cam=True, is_false_detection_images=True, num_false_detection_images=10):
     stride, names, pt = model.stride, model.names, model.pt
 
     # Load image
@@ -104,35 +104,39 @@ def inference(input_img, conf_thres, iou_thres, is_false_detection_images=True,
     else:
         misclassified_images = None
 
-    img_GC = cv2.resize(input_img, (640, 640))
-    rgb_img = img_GC.copy()
-    img_GC = np.float32(img_GC) / 255
-    transform = transforms.ToTensor()
-    tensor = transform(img_GC).unsqueeze(0)
+    if is_eigen_cam:
+        img_GC = cv2.resize(input_img, (640, 640))
+        rgb_img = img_GC.copy()
+        img_GC = np.float32(img_GC) / 255
+        transform = transforms.ToTensor()
+        tensor = transform(img_GC).unsqueeze(0)
 
-    cam = EigenCAM(model, target_layers)
-    grayscale_cam = cam(tensor)[0, :, :]
-    cam_image = show_cam_on_image(img_GC, grayscale_cam, use_rgb=True)
+        cam = EigenCAM(model, target_layers)
+        grayscale_cam = cam(tensor)[0, :, :]
+        cam_image = show_cam_on_image(img_GC, grayscale_cam, use_rgb=True)
+    else:
+        cam_image = None
 
     return img0, cam_image, misclassified_images
 
 title = "YOLOv9 model to detect shirt/tshirt"
 description = "A simple Gradio interface to infer on YOLOv9 model and detect tshirt in image"
-examples = [["image_1.jpg", 0.25, 0.45, True, 10],
-            ["image_2.jpg", 0.25, 0.45, True, 10],
-            ["image_3.jpg", 0.25, 0.45, True, 10],
-            ["image_4.jpg", 0.25, 0.45, True, 10],
-            ["image_5.jpg", 0.25, 0.45, True, 10],
-            ["image_6.jpg", 0.25, 0.45, True, 10],
-            ["image_7.jpg", 0.25, 0.45, True, 10],
-            ["image_8.jpg", 0.25, 0.45, True, 10],
-            ["image_9.jpg", 0.25, 0.45, True, 10],
-            ["image_10.jpg", 0.25, 0.45, True, 10]]
+examples = [["image_1.jpg", 0.25, 0.45, True, True, 10],
+            ["image_2.jpg", 0.25, 0.45, True, True, 10],
+            ["image_3.jpg", 0.25, 0.45, True, True, 10],
+            ["image_4.jpg", 0.25, 0.45, True, True, 10],
+            ["image_5.jpg", 0.25, 0.45, True, True, 10],
+            ["image_6.jpg", 0.25, 0.45, True, True, 10],
+            ["image_7.jpg", 0.25, 0.45, True, True, 10],
+            ["image_8.jpg", 0.25, 0.45, True, True, 10],
+            ["image_9.jpg", 0.25, 0.45, True, True, 10],
+            ["image_10.jpg", 0.25, 0.45, True, True, 10]]
 
 demo = gr.Interface(inference, 
                     inputs = [gr.Image(width=320, height=320, label="Input Image"), 
                               gr.Slider(0, 1, 0.25, label="Confidence Threshold"),
                               gr.Slider(0, 1, 0.45, label="IoU Thresold"),
+                              gr.Checkbox(label="Show Eigen CAM"),
                               gr.Checkbox(label="Show False Detection"),
                               gr.Slider(5, 35, value=10, step=5, label="Number of False Detection")],
                     outputs= [gr.Image(width=640, height=640, label="Output"),