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1. Top results related to define bit depth in python

   • how can change 24 bit depth to 8 bit depth in python in pillow?

     Top Answer

     Answered Apr 04, 2022 · 3 votes

     convert() doesn't change original image in img but it creates new image which you have to assign to variable - if you assign to the same variable img then you replace original image.

     img = img.convert(...)-

     That's all.

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     1/5

   • Determine MP3 bit depth in Python via Mutagen

     Top Answer

     Answered Jun 24, 2010 · 4 votes

     The transformations done by the MP3 encoding process drop completely the concept of “bit depth”. You can only know the bit depth of the source audio if such information was stored in a tag of the MP3 file. Otherwise, you can take the MP3 data and produce 8-bit, 16-bit or 24-bit audio.

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     2/5

   • Depth Traversing a graph in Python

     Top Answer

     Answered Jan 15, 2016 · 1 votes

     This below already visits all nodes.

     graph = {'A': ['B', 'C'], 'B': ['A', 'F'], 'C': ['D', 'E'], 'D': ['H', 'J', 'C'], 'E': ['C', 'F'], 'F': ['B', 'G'], 'G': ['F', 'H'], 'H': ['G', 'D', 'I'], 'I': ['H', 'K'], 'J': ['D', 'E', 'K'], 'K': ['I', 'J']}current_node = []viewed_nodes = []def traverse(into): if into in viewed_nodes: return viewed_nodes.append(into) for outto in graph[into]: if outto not in viewed_nodes: traverse(outto)for node in graph: traverse(node)print(sorted(viewed_nodes))

     Output:

     ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']-

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     3/5

   • Depth First Search in Python (including cycles)

     Top Answer

     Answered Feb 05, 2015 · 2 votes

     As mentioned in the comment, your algorithm has no reason to terminate if you allow arbitrary cycles. What you could do is allow for a maximum path length and dismiss all paths that are too long:

     def find_all_paths(graph, start, end, path=[], max_length=10): if len(path) >= max_length: return [] path = path + [start] if start == end: return [path] if start not in graph: return [] paths = [] for node in graph[start]: paths += find_all_paths(graph, node, end, path, max_length=max_length) return paths

     with

     graph = {'Start': ['1'], '1': ['2'], '2': ['3','End'], '3': ['2','End']}print find_all_paths(graph, 'Start', 'End', max_length=10)

     your algorithm prints:

     [['Start', '1', '2', '3', '2', '3', '2', '3', '2', 'End'], ['Start', '1', '2', '3', '2', '3', '2', '3', 'End'], ['Start', '1', '2', '3', '2', '3', '2', 'End'], ['Start', '1', '2', '3', '2', '3', 'End'], ['Start', '1', '2', '3', '2', 'End'], ['Start', '1', '2', '3', 'End'], ['Start', '1', '2', 'End']]-

     EDIT:

     Replaced not graph.has_key with the more pythonic start not in graph

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     4/5

   • Depth-first search (DFS) code in python

     Top Answer

     Answered Jul 28, 2017 · 19 votes

     I think you have an indentation problem there. Assuming your code looks like this:

     graph1 = { 'A' : ['B','S'], 'B' : ['A'], 'C' : ['D','E','F','S'], 'D' : ['C'], 'E' : ['C','H'], 'F' : ['C','G'], 'G' : ['F','S'], 'H' : ['E','G'], 'S' : ['A','C','G']}visited = []def dfs(graph,node): global visited if node not in visited: visited.append(node) for n in graph[node]: dfs(graph,n)dfs(graph1,'A')print(visited)

     I would say a couple of things:

     • Avoid globals if you can
     • Instead of a list for visited, use a set

     plus:

     • This will not work for forests but I assume you already know that
     • It will fail if you reference a node that does not exist.

     Updated code:

     graph1 = { 'A' : ['B','S'], 'B' : ['A'], 'C' : ['D','E','F','S'], 'D' : ['C'], 'E' : ['C','H'], 'F' : ['C','G'], 'G' : ['F','S'], 'H' : ['E','G'], 'S' : ['A','C','G']}def dfs(graph, node, visited): if node not in visited: visited.append(node) for n in graph[node]: dfs(graph,n, visited) return visitedvisited = dfs(graph1,'A', [])print(visited)

     Other Answers

     Answered Aug 16, 2022 · 13 votes

     Without recursion:

     def dfs(graph, node): visited = set((node,)) output = [node] stack = [node] while stack: node = stack[-1] if node not in visited: output.append(node) visited.add(node) remove_from_stack = True for next_node in graph[node]: if next_node not in visited: stack.append(next_node) remove_from_stack = False break if remove_from_stack: stack.pop() return outputprint (dfs(graph1, 'A'))

     Output:

     ['A', 'B', 'S', 'C', 'D', 'E', 'H', 'G', 'F']-

     Other Answers

     Answered Aug 04, 2022 · 5 votes

     Here's an iterative (non-recursive) implementation of a DFS:

     def dfs_iterative(graph, start_vertex): visited = set() traversal = [] stack = [start_vertex] while len(stack) > 0: vertex = stack.pop() if vertex not in visited: visited.add(vertex) traversal.append(vertex) stack.extend(reversed(graph[vertex])) # add vertex in the same order as visited return traversaltest_graph = { 'A' : ['B','S'], 'B' : ['A'], 'C' : ['D','E','F','S'], 'D' : ['C'], 'E' : ['C','H'], 'F' : ['C','G'], 'G' : ['F','S'], 'H' : ['E','G'], 'S' : ['A','C','G']}print(dfs_iterative(test_graph, 'A'))

     Output:

     ['A', 'B', 'S', 'C', 'D', 'E', 'H', 'G', 'F']

     Check all answers on Stack Overflow

     5/5

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2. bioimagebook.github.io › 3-bit_depths › pythonPython: Types & bit-depths — Introduction to Bioimage Analysis

   bioimagebook.github.io › 3-bit_depths › python

   • Cached

   In this section, we will explore how bit-depths and image types are represented in Python. We’ll look in particular at where things can go wrong when converting between bit-depths, and how to apply the tricks from previous chapters to identify problems.

3. stackoverflow.com › questions › 1996577python - How can I get the depth of a jpg file? - Stack Overflow

   stackoverflow.com › questions › 1996577

   • Cached

   I want to retrieve the bit depth for a jpeg file using Python. Using the Python Imaging Library: import Image data = Image.open('file.jpg') print data.depth However, this gives me a depth of 8 f...

   Code sample

   mode_to_bpp = {'1':1, 'L':8, 'P':8, 'RGB':24, 'RGBA':32, 'CMYK':32, 'YCbCr':24, 'I':32, 'F':32}

   data = Image.open('file.jpg')

   bpp = mode_to_bpp[data.mode]

   See more on stackoverflow

4. medium.com › @microbioscopicdata › bio-image(Bio)Image Analysis with Python: Everything You Need ... - Medium

   medium.com › @microbioscopicdata › bio-image

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   Jan 2, 2024 · In this tutorial, we will use the power of Python to illuminate the significance of image bit-depth in the context of microscopy. We’ll use practical examples to simplify the understanding...

5. realpython.com › python-bitwise-operatorsBitwise Operators in Python – Real Python

   realpython.com › python-bitwise-operators

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   Python’s bitwise operators let you manipulate those individual bits of data at the most granular level. You can use bitwise operators to implement algorithms such as compression, encryption, and error detection as well as to control physical devices in your Raspberry Pi project or elsewhere.

6. scikit-image.org › docs › stable5. Image data types and what they mean — skimage 0.23.2 ...

   scikit-image.org › docs › stable

   • Cached

   For example, some cameras store images with 10-, 12-, or 14-bit depth per pixel. If these images are stored in an array with dtype uint16, then the image won’t extend over the full intensity range, and thus, would appear dimmer than it should.

7. pillow.readthedocs.io › en › stableConcepts - Pillow (PIL Fork) 10.3.0 documentation

   pillow.readthedocs.io › en › stable

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   The Python Imaging Library allows you to store several bands in a single image, provided they all have the same dimensions and depth. For example, a PNG image might have ‘R’, ‘G’, ‘B’, and ‘A’ bands for the red, green, blue, and alpha transparency values.

8. People also ask

   What is bit-length in Python?

   • Notice that bit-length, which is the number of binary digits, varies greatly across the characters. The euro sign ( €) requires fourteen bits, while the rest of the characters can comfortably fit on seven bits. Note: Here’s how you can check the bit-length of any integer number in Python:

   Bitwise Operators in Python – Real Python

   realpython.com/python-bitwise-operators/

   See all results for this question

   How many BPP is a Python depth attribute?

   • Yeah it's 8 bpp. What wasn't obvious (to me) was that it was for each band as per Mike's answer. I don't see the depth attribute documented anywhere in the Python Imaging Library handbook. However, it looks like only a limited number of modes are supported. You could use something like this:

   python - How can I get the depth of a jpg file? - Stack Overflow

   stackoverflow.com/questions/1996577/how-can-i-get-the-depth-of-a-jpg-file

   See all results for this question

   How do bitwise operations work in Python?

   • Bitwise operations on Python ints work much like in C. The &, | and ^ operators in Python work just like in C. The ~ operator works as for a signed integer in C; that is, ~x computes -x-1. You have to be somewhat careful with left shifts, since Python integers aren't fixed-width. Use bit masks to obtain the low order bits.

   How do I manipulate bits in Python? - Stack Overflow

   stackoverflow.com/questions/147713/how-do-i-manipulate-bits-in-python

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   How do I use bit manipulation in Python?

   • Python has C style bit manipulation operators, so your example is literally the same in Python except without type keywords. You should also check out BitArray, which is a nice interface for dealing with sequences of bits. Omit the 'unsigned long', and the semi-colons are not needed either:

   How do I manipulate bits in Python? - Stack Overflow

   stackoverflow.com/questions/147713/how-do-i-manipulate-bits-in-python

   See all results for this question

9. bioimagebook.github.io › bit_depthsTypes & bit-depths — Introduction to Bioimage Analysis

   bioimagebook.github.io › bit_depths

   • Cached

   The bit-depth of an image is the number of bits used to represent each pixel. A bit-depth of 8 would indicate that 8 bits are used to represent a single pixel value. The bit-depth imposes a limit upon the pixel values that are possible.