Category : transform

When loading an old xgboost vectorizer, i’m getting the following error: AttributeError: ‘XGBClassifier’ object has no attribute ‘transform’ funnel_model = pickle.load(open(project_directory +language+’/funnel_japan.sav’, ‘rb’)) xvalid_count_source = embeddings.transform(funneldf[‘cleaned_original_text’].apply(lambda x: np.str_(x))) The code was originally created a year ago using an xgboost==0.90 model but the new model was trained using xgboost==1.4.2. Oddly enough the same .transform works later ..

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I am getting this error while doing the transform task in iraf. transform input=hd75555lr_s0.5nhg_combine output=hd75555lr_s0.5nhg_combine_t fitnames=arglamplowr_s1.0-00053.Z-CROP interptype=linear flux=yes blank=INDEF x1=INDEF x2=INDEF dx=INDEF y1=INDEF y2=INDEF dy=INDEF Killing IRAF task `transform’ Traceback (innermost last): File "CL script CL1", line 1, in module IrafError: Error running IRAF task transform IRAF task terminated abnormally ERROR (741, "Cannot open file ..

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I am trying to reconstruct the details and approximations at all levels using the inverse Stationary Wavelet Transform. The code is the following: def decompose_B(Btotal, wname, Lps, Hps): Br = Btotal[0]; Bt = Btotal[1]; Bn = Btotal[2] ## Set parameters needed for UDWT samplelength=len(Br) # If length of data is odd, turn into even numbered ..

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I Create function to log transform an image in python. Below is my code.. #Compute Log Only def logTransform(c, f): g = c * m.log(float(1+f)) return g def ImgLogarithmic (img_input, coldepth): #logarithmatic transform inputMax = 255 outputMax = 255 c = outputMax/m.log(inputMax+1) if coldepth != 24: img_input = img_input.convert(‘RGB’) img_output = Image.new(‘RGB’, (img_input.size[1], img_input.size[0])) pixels ..

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I’m facing a strange issue here. So my purpose is to draw a rectangle below one image and text wrapped around this image. I then created a new axis and place the two strings on the top and right of it (using the transform=ax_img.transAxes option). Then I use the r = fig.canvas.get_renderer() and get_window_extent(renderer=r) functions ..

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I am a beginner in PyTorch. I want to train a network using NYU dataset, but I am getting an error. The error happens while I use the Dataloader to load my local dataset, and I want to print the data to demonstrate the code is right: test=Mydataset(data_root,transforms,’image_train’) test2=DataLoader(test,batch_size=4,num_workers=0,shuffle=False) for idx,data in enumerate(test2): print(idx) Here’s ..

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