create app.py

app.py

@@ -0,0 +1,87 @@
+# gradioMisClassGradCAMimageInputter
+import numpy as np
+import gradio as gr
+from PIL import Image
+from pytorch_grad_cam import GradCAM
+from pytorch_grad_cam.utils.image import show_cam_on_image
+from torchvision import datasets, transforms, utils
+
+fileName = None
+
+def hello(DoYouWantToShowMisClassifiedImages, HowManyImages):
+  if(DoYouWantToShowMisClassifiedImages.lower() == "yes"):
+    fileName = misclas_helper.display_cifar_misclassified_data(misclassified_data, classes, inv_normalize, number_of_samples=HowManyImages)
+    return Image.open(fileName)
+  else:
+    return None
+misClass_demo = gr.Interface(
+    fn = hello,
+    inputs=['text', gr.Slider(0, 20, step=5)],
+    outputs=['image'],
+    title="Misclasseified Images",
+    description="If your answer to the question DoYouWantToShowMisClassifiedImages is yes, then only it works.",
+)
+
+
+############
+
+targets = None
+device = torch.device("cpu")
+classes = ('plane', 'car', 'bird', 'cat', 'deer',
+           'dog', 'frog', 'horse', 'ship', 'truck')
+
+
+def inference(DoYouWantToShowGradCAMMedImages, HowManyImages, WhichLayer, transparency):
+  if(DoYouWantToShowGradCAMMedImages.lower() == "yes"):
+    if(WhichLayer == -1):
+      target_layers = [model.model.resNetLayer2Part2[-1]]
+    elif(WhichLayer == -2):
+      target_layers = [model.model.resNetLayer2Part1[-1]]
+    elif(WhichLayer == -3):
+      target_layers = [model.model.Layer3[-1]]
+    fileName = gradcam_helper.display_gradcam_output(misclassified_data, classes, inv_normalize, model.model, target_layers, targets, number_of_samples=HowManyImages, transparency=0.70)
+    return Image.open(fileName)
+
+gradCAM_demo = gr.Interface(
+    fn=inference,
+        #DoYouWantToShowGradCAMMedImages, HowManyImages, WhichLayer, transparency
+    inputs=['text', gr.Slider(0, 20, step=5), gr.Slider(-3, -1, value = -1, step=1), gr.Slider(0, 1, value = 0.7, label = "Overall Opacity of the Overlay")],
+    outputs=['image'],
+    title="GradCammd Images",
+    description="If your answer to the question DoYouWantToShowGradCAMMedImages is yes, then only it works.",
+)
+
+
+############
+
+def ImageInputter(img1, img2, img3, img4, img5, img6, img7, img8, img9, img10):
+  return img1, img2, img3, img4, img5, img6, img7, img8, img9, img10
+
+imageInputter_demo = gr.Interface(
+    ImageInputter,
+    [
+        "image","image","image","image","image","image","image","image","image","image"
+    ],
+    [
+        "image","image","image","image","image","image","image","image","image","image"
+    ],
+    examples=[
+        ["bird.jpg", "car.jpg", "cat.jpg"],
+        ["deer.jpg", "dog.jpg", "frog.jpg"],
+        ["horse.jpg", "plane.jpg", "ship.jpg"],
+        [None, "truck.jpg", None],
+    ],
+    title="Max 10 images input",
+    description="Here's a sample image inputter. Allows you to feed in 10 images and display them. You may drag and drop images from bottom examples to the input feeders",
+)
+
+
+############
+
+
+demo = gr.TabbedInterface(
+    interface_list = [misClass_demo, gradCAM_demo, imageInputter_demo],
+    tab_names = ["MisClassified Images", "GradCAMMed Images", "10 images inputter"]
+)
+
+demo.launch(debug=True)