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Doesn't work with single row/column dataset #430

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sTeADone opened this issue Mar 14, 2024 · 0 comments
Open

Doesn't work with single row/column dataset #430

sTeADone opened this issue Mar 14, 2024 · 0 comments

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@sTeADone
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Works pretty well if the source contains multiple columns and rows.
Gives error if only one column or row is selected for stitching.

test2.zip

import numpy as np
import os
import pandas as pd
import m2stitch
import cv2

props = pd.read_csv("list.csv", index_col=0)

# filter columns/rows

# this works
sub_props = props[props["col"].isin([0,1])]

# this will fail
# sub_props = props[props["col"].isin([1])]

print(sub_props.index.to_list())
print(sub_props["col"].to_list())
print(sub_props["row"].to_list())

images = []
for idx,row in sub_props.iterrows():
    path = os.path.join("./imgs",row["file"])
    print(path)
    grey = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
    print(grey.shape)
    images.append(grey)

result_df, _ = m2stitch.stitch_images(
    images, sub_props["row"].to_list(), sub_props["col"].to_list(), row_col_transpose=False, ncc_threshold=0.2
)

# merge with original to get the file name
result_df = result_df.merge(sub_props, on=["row", "col"])

def output_image(images, result_df, filename):
    result_df["y_pos2"] = result_df["y_pos"] - result_df["y_pos"].min()
    result_df["x_pos2"] = result_df["x_pos"] - result_df["x_pos"].min()

    size_y = images[0].shape[0]
    size_x = images[0].shape[1]

    stitched_image_size = (
        result_df["y_pos2"].max() + size_y,
        result_df["x_pos2"].max() + size_x,
    )
    stitched_image = np.zeros_like(images, shape=stitched_image_size)
    for i, row in result_df.iterrows():
        stitched_image[
            row["y_pos2"] : row["y_pos2"] + size_y,
            row["x_pos2"] : row["x_pos2"] + size_x,
        ] = images[i]
        # write some text on the image
        cv2.putText(stitched_image, f"{row['file']}, R{row['row']}C{row['col']}", (row["x_pos2"] + 50, row["y_pos2"] + 50), cv2.FONT_HERSHEY_SIMPLEX, 1, 0, 3, cv2.LINE_AA)
        cv2.putText(stitched_image, f"{row['file']}, R{row['row']}C{row['col']}", (row["x_pos2"] + 50, row["y_pos2"] + 50), cv2.FONT_HERSHEY_SIMPLEX, 1, 255, 2, cv2.LINE_AA)
    
    cv2.imwrite(filename, stitched_image)

output_image(result_df=result_df, images=images, filename="result.webp")
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