`ongoing`
`v1.0` | `v1.1`(current)
`v0.1` | `v0.2`
<p align="left">
Colab Preview for Code <br>
<a href="https://colab.research.google.com/drive/1ZklXjCLbrZIACctPS4EKZ4ZnuqdjonO4?usp=sharing" target="_blank">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab">
</a>
</p>
Website for eagleview
<br>
[](https://hexronus.tech/eagleview/index.html)
# eagleview
A package for greatly increasing the visualisation of datasets, in minimal lines of code.
## Usage
```
It is advised to use `Method 1`, as the github repository is updated from time to time, it may occour that new changes are not still updated.
```
### Method 1
1. Clone the repository:
```bash
!git clone https://github.com/hexronuspi/eagleview
```
2. Upload the folder containing your images. If they are in a zip or any other file, extract them first.
3. Navigate to the cloned repository:
```
%cd eagleview
```
4. Install the package:
```
!pip install .
```
5. Use the package in your Python code:
### Method2
1. using pip install
```bash
!pip install eagleview
```
```python
import eagleview
```
<hr>
### Input:
```python
#v0.x
from eagleview.figshow import ImageMatrix
image_display = ImageMatrix('/content/path_to_folder_containing_images')
```
```python
#v1.x
from eagleview.figshow import ImageMatrix
im = ImageMatrix('/content/path_to_folder_containing_images', '/content/path_to_file_containing_label.csv')
#only .csv extension
```
### Output:
```python
#v1.0
im.rand((a, b)).display_image( # a,b is the size of matrix
check_col='col_name', # replace 'col_name' with the name of column, which has image name
display_label=True, # by default this is False
display_cols=['col1', 'col2'], # replace '', to the column name which you want to print as label
display_name=True, # by default this is False
print_all=False, # by default this is True
x= , # X-coordinate of label
y= , # Y-coordinate of label
fig_size=(m, n) # by default this is set to max(image_size), maximum size of all the images which will be displayed
)
```
```python
#v0.2
(ImageMatrix('/content/path_to_folder_containing_images').rand()).display_image((2,2), print_all=False, display_name=True)
```
```python
# v0.1
(ImageMatrix('/content/path_to_folder_containing_images')).display_image((2,2), print_all=False)
```
## Releases:
- `v0.1`
- This will display the images in a grid with 3 columns and 2 rows, without printing the left out images. If you want to print all images, you can call `image_display.display_image((2, 3))` or `image_display.display_image((2, 3), True)`.
- `v0.2`
- This will display the name of the images, as their titles. In v0.1, the images were printed starting from first and consecutive until upper bound is reached, this is an optional and random option is added.
- `v1.0`
- Added capability to display label with a variey of options.
- `v1.1`
- Added capability to change label display and visuals with a variey of options.
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"description": "`ongoing` \n\n`v1.0` | `v1.1`(current)\n\n`v0.1` | `v0.2`\n\n\n\n <p align=\"left\">\n Colab Preview for Code <br>\n <a href=\"https://colab.research.google.com/drive/1ZklXjCLbrZIACctPS4EKZ4ZnuqdjonO4?usp=sharing\" target=\"_blank\">\n <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\">\n </a>\n \n </p>\n\nWebsite for eagleview\n<br>\n[](https://hexronus.tech/eagleview/index.html)\n\n# eagleview\n\nA package for greatly increasing the visualisation of datasets, in minimal lines of code.\n\n## Usage\n```\nIt is advised to use `Method 1`, as the github repository is updated from time to time, it may occour that new changes are not still updated.\n```\n### Method 1\n1. Clone the repository:\n\n```bash\n!git clone https://github.com/hexronuspi/eagleview\n```\n2. Upload the folder containing your images. If they are in a zip or any other file, extract them first.\n\n3. Navigate to the cloned repository:\n\n```\n%cd eagleview\n```\n\n4. Install the package:\n\n```\n!pip install .\n```\n\n5. Use the package in your Python code:\n\n### Method2\n\n1. using pip install\n```bash\n!pip install eagleview\n```\n```python\nimport eagleview\n```\n\n<hr>\n\n\n### Input:\n\n```python\n#v0.x\nfrom eagleview.figshow import ImageMatrix\n\nimage_display = ImageMatrix('/content/path_to_folder_containing_images')\n```\n\n\n```python\n#v1.x\nfrom eagleview.figshow import ImageMatrix\n\nim = ImageMatrix('/content/path_to_folder_containing_images', '/content/path_to_file_containing_label.csv')\n#only .csv extension\n```\n\n### Output:\n```python\n#v1.0\nim.rand((a, b)).display_image( # a,b is the size of matrix\n check_col='col_name', # replace 'col_name' with the name of column, which has image name\n display_label=True, # by default this is False\n display_cols=['col1', 'col2'], # replace '', to the column name which you want to print as label\n display_name=True, # by default this is False\n print_all=False, # by default this is True\n x= , # X-coordinate of label\n y= , # Y-coordinate of label\n fig_size=(m, n) # by default this is set to max(image_size), maximum size of all the images which will be displayed\n)\n\n```\n```python\n#v0.2\n(ImageMatrix('/content/path_to_folder_containing_images').rand()).display_image((2,2), print_all=False, display_name=True)\n```\n```python\n# v0.1\n(ImageMatrix('/content/path_to_folder_containing_images')).display_image((2,2), print_all=False)\n```\n\n## Releases: \n- `v0.1`\n - This will display the images in a grid with 3 columns and 2 rows, without printing the left out images. If you want to print all images, you can call `image_display.display_image((2, 3))` or `image_display.display_image((2, 3), True)`.\n \n- `v0.2`\n - This will display the name of the images, as their titles. In v0.1, the images were printed starting from first and consecutive until upper bound is reached, this is an optional and random option is added.\n \n- `v1.0`\n - Added capability to display label with a variey of options.\n \n- `v1.1`\n - Added capability to change label display and visuals with a variey of options.\n",
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