首先要介绍的是 Python Imaging Library,使用方法如下:
from PIL import Image
from PIL.ExifTags import TAGS
def get_exif_data(fname):
"""Get embedded EXIF data from image file."""
ret = {}
try:
img = Image.open(fname)
if hasattr( img, '_getexif' ):
exifinfo = img._getexif()
if exifinfo != None:
for tag, value in exifinfo.items():
decoded = TAGS.get(tag, tag)
ret[decoded] = value
except IOError:
print 'IOERROR ' + fname
return ret
if __name__ == '__main__':
fileName = 'C:/Users/Leyond/Desktop/IMG_20121122_153514.jpg'
exif = get_exif_data(fileName)
print exif
返回的清单如下:
ExifVersion
ComponentsConfiguration
ExifImageWidth
DateTimeOriginal
DateTimeDigitized
ExifInteroperabilityOffset
FlashPixVersion
MeteringMode
LightSource
Flash
FocalLength
41986
ImageDescription
Make
Model
Orientation
YCbCrPositioning
41988
XResolution
YResolution
59932
ExposureTime
ExposureProgram
ColorSpace
41990
ISOSpeedRatings
ResolutionUnit
41987
FNumber
Software
DateTime
ExifImageHeight
ExifOffset
其中59932,是一大串十六进制的字符,不知为啥。除了PIL之外,还有许多类库可供使用:
Media Metadata for Python
EXIF.py
Python Exif Parser
A Blogger's Exif Parser
pyexiv2
接着看EXIF.PY,使用方法非常简单:exif.py IMG_20121122_153514.jpg
EXIF ColorSpace (Short): sRGB
EXIF ComponentsConfiguration (Undefined): YCbCr
EXIF DateTimeDigitized (ASCII): 2012:11:22 15:35:14
EXIF DateTimeOriginal (ASCII): 2012:11:22 15:35:14
EXIF DigitalZoomRatio (Ratio): 1
EXIF ExifImageLength (Long): 2560
EXIF ExifImageWidth (Long): 1920
EXIF ExifVersion (Undefined): 0220
EXIF ExposureBiasValue (Signed Ratio): 0
EXIF ExposureMode (Short): Auto Exposure
EXIF ExposureProgram (Short): Portrait Mode
EXIF ExposureTime (Ratio): 1/256
EXIF FNumber (Ratio): 14/5
EXIF Flash (Short): Flash did not fire
EXIF FlashPixVersion (Undefined): 0100
EXIF FocalLength (Ratio): 35
EXIF ISOSpeedRatings (Short): 56
EXIF InteroperabilityOffset (Long): 4810
EXIF LightSource (Short): other light source
EXIF MeteringMode (Short): CenterWeightedAverage
EXIF Padding (Undefined): []
EXIF SceneCaptureType (Short): Portrait
EXIF WhiteBalance (Short): Auto
Image DateTime (ASCII): 2012:11:24 09:44:50
Image ExifOffset (Long): 2396
Image ImageDescription (ASCII):
Image Make (ASCII):
Image Model (ASCII):
Image Orientation (Short): Horizontal (normal)
Image Padding (Undefined): []
Image ResolutionUnit (Short): Pixels/Inch
Image Software (ASCII): Microsoft Windows Photo Viewer 6.1.7600.16385
Image XResolution (Ratio): 72
Image YCbCrPositioning (Short): Co-sited
Image YResolution (Ratio): 72
Thumbnail Compression (Short): JPEG (old-style)
Thumbnail JPEGInterchangeFormat (Long): 4970
Thumbnail JPEGInterchangeFormatLength (Long): 3883
Thumbnail Orientation (Short): Horizontal (normal)
Thumbnail ResolutionUnit (Short): Pixels/Inch
Thumbnail XResolution (Ratio): 72
Thumbnail YCbCrPositioning (Short): Co-sited
Thumbnail YResolution (Ratio): 72
至于Python Exif Parser,好像没更新很久了,使用方法也很类似:
import exif
photo_path = "somePath\to\a\photo.jpg"
data = exif.parse(photo_path)
其他类库请自行研究。

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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