mention changes in v2 + add tips and trick to readme

Author: Laurent Thomas

CHANGELOG.md

@@ -3,11 +3,25 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).  
 
+## [2.0.0] - 2024-
+
+### Added
+- Type hints for function parameters for most functions
+
+### Changed
+- functions uses/returns list of detected hits as a list of tuple : 1 tuple per hit in the form (label, (x,y,width,height), score) 
+it does not return pandas.DataFrame anymore
+
+## Removed
+- dependency on pandas
+
+
 ## [1.6.6] - 2023-08-31 
 
 ### Changed 
 - Changed licence to MIT
 
+
 ## [1.6.5] - 2023-06-12
 
 ### Changed
@@ -45,6 +59,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
 
 ## [1.6.1] - 2020-08-20
+
 ### Added
 - support mask for matchTemplates and findMatches as in cv2.matchTemplates with method 0 or 3
 - notebook tutorial with mask
@@ -53,43 +68,55 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 ### Changed
 - better docstrings
 
+
 ## [1.6.0.post1] - 2020-08-04
+
 ### Fixed
 - issue when no detection found (see Changed of version 1.5.3.post2)
 
 
 ## [1.6.0] - 2020-08-03
+
 ### Changed
 - NMS is now using the opencv `cv2.dnn.NMSBoxes` function
 - use timeit for benchmark in example notebook
 
 ### Removed
 - `MTM.NMS.Point_in_Rectangle` and `MTM.NMS.computeIoU` as they are not used anymore for the NMS
 
+
 ## [1.5.3.post2] - 2020-08-04
+
 ### Fixed
 - issue when no detection found (see Changed)
 
 ### Changed
 - `MTM.findMatches` return a dataframe with proper column names (not just empty)
 - better handle the different opencv matchTemplate methods
 
+
 ## [1.5.3.post1] - 2020-05-11
+
 ### Removed
 - remove the hardcoded version requirement for opencv-python-headless in setup.py
 
 ### Added
 - MTM version is now defined in a dedicated version.py file
 
+
 ## [1.5.3] - 2020-04-28
+
 ### Added
 - `MTM.computeScoreMap` which is like `cv2.matchTemplate` but checking for image types
 
 
 ## [1.5.2] - 2019-12-19
+
 ### Changed
 - `MTM.findMatches` automatically cast 16-bit images and/or template to 32-bit
 
+
 ## [1.5.1] - 2019-10-10  
+
 ### Changed
 - use pandas dataframe to return list of hits for `MTM.matchTemplates` and `MTM.findMatches` 

README.md

@@ -9,6 +9,7 @@ The main function `MTM.matchTemplates` returns the best predicted locations prov
 The branch opencl contains some test using the UMat object to run on GPU, but it is actually slow, which can be expected for small dataset as the transfer of the data between the CPU and GPU is slow.
 
 # News
+- Version 2.0.0 got rid of the dependency on pandas, the list of hit is simply a python list. The new version also features extensive type hints in functions
 - 03/03/2023 : Version 1.6.4 contributed by @bartleboeuf comes with speed enhancement thanks to parallelizing of the individual template searches.
 Thanks for this first PR !!
 - 10/11/2021 : You might be interested to test the newer python implementation which is more object-oriented and only relying on scikit-image and shapely.*
@@ -29,6 +30,26 @@ Then opening a command prompt in the repo's root directory (the one containing t
 The [wiki](https://github.com/multi-template-matching/MultiTemplateMatching-Python/wiki) section of the repo contains a mini API documentation with description of the key functions of the package.   
 The [website](https://multi-template-matching.github.io/Multi-Template-Matching/) of the project contains some more general documentation.
 
+# Tips and tricks
+- To have a nicer formatting when printing the list of detected hits, you can wrap it into a numpy array, and print that array as following  
+`print(np.array(listHit, dtype=object))`, the `dtype=object` argument is required as each hit in the list is made of different data type (string, tuple and float)
+
+- Before version 2.0.0, most functions were returning or accepting pandas DataFrame for the list of hit.  
+You can still get such DataFrame from the list of hit returned by the newer version of the package, using these commands  
+
+```python
+import pandas as pd
+
+listLabel = [hit[0] for hit in listHit]
+listBbox  = [hit[1] for hit in listHit]
+listScore = [hit[2] for hit in listHit]
+
+df = pd.DataFrame({"Label":listLabel,
+				   "bounding box":listBbox,
+				   "Score":listScore})
+
+print(df)
+```
 
 # Examples
 Check out the [jupyter notebook tutorial](https://github.com/multi-template-matching/MultiTemplateMatching-Python/tree/master/tutorials) for some example of how to use the package.