again switched to softmax as exp was crossing confidence leavel over 100

app.py

@@ -32,11 +32,11 @@ def inference(input_img, transparency = 0.5, target_layer_number = -1, num_top_c
     # input_img = input_img
     input_img = input_img.unsqueeze(0)
     outputs = model(input_img)
-    # softmax = torch.nn.Softmax(dim=0)
-    # o = softmax(outputs.flatten())
-    exp_outputs = torch.exp(outputs.flatten())
-    # confidences = {classes[i]: float(o[i]) for i in range(10)}
-    confidences = {classes[i]: float(exp_outputs[i]) for i in range(10)}
+    softmax = torch.nn.Softmax(dim=0)
+    o = softmax(outputs.flatten())
+    # exp_outputs = torch.exp(outputs.flatten())
+    confidences = {classes[i]: float(o[i]) for i in range(10)}
+    # confidences = {classes[i]: float(exp_outputs[i]) for i in range(10)}
     _, prediction = torch.max(outputs, 1)
     target_layers = [model.layer3_r3[target_layer_number]]
     cam = GradCAM(model=model, target_layers=target_layers, use_cuda=False)