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How can I modify the [gradcam_yolov3.py](https://github.com/RuoyuChen10/objectdetection-saliency-maps/blob/main/tutorial/gradcam-yolov3.ipynb) to use in RetinaNet?
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嗨,我尝试运行RetinaNet示例代码。 该程序开始运行,但不久后失败。 那是最后几行:
Hi, I tried to run the RetinaNet sample code. The program started to run, but failed shortly after. Those are the last few lines:
```python
feature s…
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Due to popularity of inception network, let's see if it is possible visualizing inception network with GradCAM.
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### **This is my code:**
`model = model.to("cuda")
def load_image(image_path = "Normal-3000.png"):
raw_image = cv2.imread(image_path)
raw_image = cv2.resize(raw_image, (224,) * 2)
ima…
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Currently, encoder-decoder models lack support for Grad-CAM (Gradient-weighted Class Activation Mapping) visualization with cross-attention mechanisms. Grad-CAM is a valuable tool for interpreting mo…
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Thank you for your great work and your excellent and responsible answers! But I have a question. Regarding the drawing of feature heat maps in your paper, can you provide the code?
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https://github.com/pytorch/captum/blob/43acfcd320c44e8e469bf5276af9d55cf62145aa/captum/attr/_core/guided_grad_cam.py#L211
If I understand corretly, the parameter here should be:
inputs[i].shape[1…
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I'm working with a multi-label image dataset. My inputs have the following shape: ``torch.Size([3, 224, 224])``; and my targets are all 1x33 tensors one-hot encoded, as in the following example:
``
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Hi,
I would highly appreciate any sample code for how can we use tf Explain GradCam feature for tensorflow dataset.
Best Regard
Vishal