merge V03 with V04

.github/workflows/docker-publish.yml

@@ -35,11 +35,20 @@ jobs:
           password: ${{ secrets.DOCKER_PWORD }}
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v1
-
+
+     # - name: Get script version
+        #id: version
+        #run: echo "{version}=${(python mindagap.py -v)}" >> $GITHUB_STATE    # This give error: bad substitution
+
       - name: Build and push
+        id: docker_build
         uses: docker/build-push-action@v2
         with:
           context: .
           file: ./Dockerfile
           push: ${{ github.event_name != 'pull_request' }}
           tags: ${{ secrets.DOCKER_USERNAME }}/mindagap:${{github.sha}}, ${{ secrets.DOCKER_USERNAME }}/mindagap:latest
+
+          #        ${{ secrets.DOCKER_USERNAME }}/mindagap:${{steps.version.outputs.version}}
+
+

Dockerfile

@@ -4,4 +4,11 @@ RUN micromamba install -y -n base -f /tmp/env.yaml && \
     micromamba clean --all --yes
 ARG MAMBA_DOCKERFILE_ACTIVATE=1
 WORKDIR /mindagap
-COPY . .
+COPY . .
+
+
+# Set a label with the version information
+#ARG VERSION
+#LABEL version=$VERSION
+
+#CMD ["python", "mindagap.py", "-v"]  # Seems to give error of uninstalled library

README.md

@@ -1,4 +1,8 @@
-# MindaGap
+# MindaGap 
+
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8120559.svg)](https://doi.org/10.5281/zenodo.8120559)
+
+
    Takes a single panorama image and fills the empty grid lines with neighbour-weighted values.
    Small box sizes yield limited results but work the best with a high loop number (like 40).  Increase boxsize to overcome bigger gaps.
 
@@ -76,3 +80,8 @@ docker build -t mindagap .
 docker run --rm -it mindagap:latest \
 python /mindagap/mindagap.py
 ```
+
+
+How to cite 
+--------------
+      Ricardo Guerreiro, Florian Wuennemann, & pvtodorov. (2023). ViriatoII/MindaGap: v0.0.3 (0.0.3). Zenodo. https://doi.org/10.5281/zenodo.8120559

env.yml

@@ -73,7 +73,9 @@ dependencies:
   - pip=22.3
   - pixman=0.40.0
   - python_abi=3.9
+  - procps-ng
   - readline=8.1.2
+  - rich
   - scipy=1.9.3
   - setuptools=65.5.0
   - six=1.16.0

mindagap.py

@@ -1,11 +1,10 @@
-doc = ''' USAGE:   python mindagap.py  <PANORAMA.tif> <boxsize> <loopnum> <tilesize> --edges <True|False> 
+doc = ''' USAGE:   python mindagap.py  <PANORAMA.tif> <boxsize> <loopnum> -xt <Xtilesize> -yt <Ytilesize> --edges <True|False> 
 
    Takes a single panorama image and fills the empty grid lines with neighbour-weighted values.
    
    Small boxsize yields limited results but works the best with a high loop number (like 20)
    Increase boxsize to overcome bigger gaps 
-   
-   <tilesize> is optional parameter to deal with adjacent tiles without gaps but where there are visible  different exposures  (EXPERIMENTAL) 
+   <tilesize> is optional parameter to deal with adjacent tiles without gaps but where there are visible different exposures  (EXPERIMENTAL) 
    
    --edges is optional parameter to blur area around grid, for smoother transitions between tiles with different exposures (EXPERIMENTAL)
    
@@ -58,9 +57,12 @@ def fill_grids(img_array, box_size = 5, nloops = 1, edges = 0, Xtilesize = None)
        for xjump in range(Xtilesize, panoXmax, Xtilesize):
            xmin,xmax = xjump -1 ,xjump + 2
            grid_coords [:,xmin:xmax] = True 
+    print("Test 2")
 
+
     if edges > 0:
          # Kernel: here you should define how much the True "dilates"
+
          expansion = np.array([[True] *edges] *edges)
 
          # Expand/dilate grid   (https://python.tutorialink.com/how-to-expand-dilate-a-numpy-array/)
@@ -69,11 +71,10 @@ def fill_grids(img_array, box_size = 5, nloops = 1, edges = 0, Xtilesize = None)
                                     expansion.astype(int), mode='same').astype(bool)
 
     # Create a blurred image and replace original grid positions by new blur value. Iterate
-    for i in range(nloops):
+    for i in track(range(nloops),description='[green]Applying Gaussian Blur to gridlines ...'):
 
         # Smooth edges as well (last loops only) if asked
         if edges and (i > nloops -5):
-            #blur_img = cv2.GaussianBlur(im_copy,(box_size,box_size), 0)  
             blur_img =  cv2.medianBlur(im_copy,box_size,cv2.BORDER_DEFAULT) 
             im_copy[expanded_grid] = blur_img[expanded_grid]     
 
@@ -92,6 +93,7 @@ def fill_grids(img_array, box_size = 5, nloops = 1, edges = 0, Xtilesize = None)
     from scipy.signal import convolve2d
     import numpy as np
     import matplotlib.pyplot as plt
+    from rich.progress import track
 
     #increase max allowed image size
     os.environ["OPENCV_IO_MAX_IMAGE_PIXELS"] = pow(2,40).__str__()
@@ -106,9 +108,10 @@ def fill_grids(img_array, box_size = 5, nloops = 1, edges = 0, Xtilesize = None)
     parser.add_argument("-r", "--rounds",    nargs = '?', type=int, default = 40, help="Number of rounds to apply gaussianBlur (more is better)")
     parser.add_argument("-xt", "--Xtilesize", nargs = '?', type=int, default = None,  help="Tile size (distance between gridlines) on X axis")
     parser.add_argument("-yt", "--Ytilesize", nargs = '?', type=int, default = None,  help="Tile size (distance between gridlines) on Y axis")
+
     parser.add_argument("-e", '--edges', nargs = '?', default = 0, help="Also smooth edges near grid lines")
-    parser.add_argument("-v", '--version', action='store_true', default = False, help="Print version number.")
-    args=parser.parse_args()
+    parser.add_argument("-v", '--version', action='store_true', default = False, help="Print version number.")    args=parser.parse_args()
+
 
     if args.sizekernel % 2 == 0:
         print("-s argument must be uneven number") ; exit()
@@ -129,20 +132,26 @@ def fill_grids(img_array, box_size = 5, nloops = 1, edges = 0, Xtilesize = None)
     # Read input as tif file or as png/jpg
     img = read_img(args.input) 
     panoYmax,panoXmax  = img.shape [-2:]
+
+    print("Test 1")
 
     # Apply fill_grids function and write to file #####
         # Work on composite images or z-layered tiffs
     if len(img.shape) > 2: 
         layers = []
         for l in range(img.shape[0]):
+
             layers.append(fill_grids(img_array=img[l,:,:], box_size = args.sizekernel, nloops= args.rounds, edges = args.edges))
         img = np.array(layers )
 
     else: # Work on 2D images
+
         img = fill_grids(img_array=img, box_size = args.sizekernel, nloops= args.rounds, edges = args.edges)
 
 
+
     # Save as tif file or as png/
+
     #cv2.imwrite(pathname + '_gridfilled' + extension, img)
 
     if 'tif' in extension: