Python imageio.imsave() Examples
The following are 30
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Example #1
Source File: collected_dataset.py From NeuralSceneDecomposition with GNU General Public License v3.0 | 6 votes |
def computeAndCacheBG(self, seqi, cami): bg_file_name = self.getBackgroundName(seqi, cami) bg_path = '/'.join(bg_file_name.split('/')[:-1]) num_samples = 50 import os names = [os.path.join(bg_path, file) for file in os.listdir(bg_path)] names_subsampled = names[0::len(names)//num_samples] image_batch = [np.array(imageio.imread(name), dtype='float32') for name in names_subsampled] image_batch = np.array(image_batch) print("Computing median of {} images".format(len(image_batch))) image_median = np.median(image_batch, axis=0) imageio.imsave(bg_file_name, image_median) print("Saved background image to {}".format(bg_file_name)) # training: 87395 # validation: # testing: 28400
Example #2
Source File: visualization_examples.py From habitat-api with MIT License | 6 votes |
def example_pointnav_draw_target_birdseye_view(): goal_radius = 0.5 goal = NavigationGoal(position=[10, 0.25, 10], radius=goal_radius) agent_position = np.array([0, 0.25, 0]) agent_rotation = -np.pi / 4 dummy_episode = NavigationEpisode( goals=[goal], episode_id="dummy_id", scene_id="dummy_scene", start_position=agent_position, start_rotation=agent_rotation, ) target_image = maps.pointnav_draw_target_birdseye_view( agent_position, agent_rotation, np.asarray(dummy_episode.goals[0].position), goal_radius=dummy_episode.goals[0].radius, agent_radius_px=25, ) imageio.imsave( os.path.join(IMAGE_DIR, "pointnav_target_image.png"), target_image )
Example #3
Source File: utils.py From dhSegment with GNU General Public License v3.0 | 6 votes |
def save_and_resize(img: np.array, filename: str, size=None, nearest: bool=False) -> None: """ Resizes the image if necessary and saves it. The resizing will keep the image ratio :param img: the image to resize and save (numpy array) :param filename: filename of the saved image :param size: size of the image after resizing (in pixels). The ratio of the original image will be kept :param nearest: whether to use nearest interpolation method (default to False) :return: """ if size is not None: h, w = img.shape[:2] ratio = float(np.sqrt(size/(h*w))) resized = cv2.resize(img, (int(w*ratio), int(h*ratio)), interpolation=cv2.INTER_NEAREST if nearest else cv2.INTER_LINEAR) imsave(filename, resized) else: imsave(filename, img)
Example #4
Source File: image2.py From ASR33 with MIT License | 6 votes |
def main(filename, width, invert, gamma, indent, chars1, chars2, title, output): # Aspect ratio is determined by the input image. # Width is determined here. img = load_image(filename, width, invert, gamma) # imageio.imsave("test.jpg", img) # Analyze the image hog_fd = process(img) if title: # title is a string # center it, and make bytes title = " " * int(indent + (width - len(title))/2) + title title = title.encode("utf-8") # Map to ASCII if not output: output = filename + ".txt" render(hog_fd, output, chars1, chars2, indent, title)
Example #5
Source File: cluster_images.py From NucleiDetectron with Apache License 2.0 | 6 votes |
def visualize_clusters_on_disk(img_df): CLUSTER_FOLDER = 'clusters30_agg_avg' os.mkdir((ROOT_DIR / 'clustering' / CLUSTER_FOLDER).as_posix()) for i in range(-1, NUM_CLUSTERS + 1): os.mkdir((ROOT_DIR / 'clustering' / CLUSTER_FOLDER / str(i)).as_posix()) img_df.apply(lambda x: imageio.imsave((ROOT_DIR / 'clustering' / CLUSTER_FOLDER / x['cluster-id'] / (x['ImageId'])).as_posix(), x['images']), axis=1) counts = img_df.groupby(['cluster-id']).size().sort_values(ascending=False) print(counts) C = list(counts.items()) C_Sorted = sorted(C, key=lambda x: x[1])
Example #6
Source File: image.py From MANet_for_Video_Object_Detection with Apache License 2.0 | 6 votes |
def check_movements(ims, bef_ims, aft_ims, processed_roidb, delta_bef_roi, delta_aft_roi): save_name = '/home/wangshiyao/Documents/testdata/'+processed_roidb[0]['image'].split('/')[-1] print 'saving images to '+save_name boxes = processed_roidb[0]['boxes'] ims.squeeze().transpose(1, 2, 0).astype(np.int8) bef_ims.squeeze().transpose(1, 2, 0).astype(np.int8) aft_ims.squeeze().transpose(1, 2, 0).astype(np.int8) delta_bef_roi = np.array(delta_bef_roi).transpose(1, 0, 2) delta_aft_roi = np.array(delta_aft_roi).transpose(1, 0, 2) for i in range(boxes.shape[0]): cv2.rectangle(ims, (int(boxes[i][0]), int(boxes[i][1])),(int(boxes[i][2]), int(boxes[i][3])),(55, 255, 155),5) bef_box = bbox_pred(boxes[i].reshape(1, -1), delta_bef_roi[i]) cv2.rectangle(bef_ims, (int(bef_box[0][0]), int(bef_box[0][1])),(int(bef_box[0][2]), int(bef_box[0][3])),(55, 255, 155),5) aft_box = bbox_pred(boxes[i].reshape(1, -1), delta_aft_roi[i]) cv2.rectangle(aft_ims, (int(aft_box[0][0]), int(aft_box[0][1])),(int(aft_box[0][2]), int(aft_box[0][3])),(55, 255, 155),5) imageio.imsave(save_name, ims) imageio.imsave(save_name.split('.')[-2]+'_bef'+'.JPEG', bef_ims) imageio.imsave(save_name.split('.')[-2]+'_aft'+'.JPEG', aft_ims)
Example #7
Source File: rgb2label.py From deepglobe_land_cover_classification_with_deeplabv3plus with MIT License | 6 votes |
def color2annotation(input_path, output_path): # image = scipy.misc.imread(input_path) # imread is deprecated in SciPy 1.0.0, and will be removed in 1.2.0. Use imageio.imread instead. image = imageio.imread(input_path) image = (image >= 128).astype(np.uint8) image = 4 * image[:, :, 0] + 2 * image[:, :, 1] + image[:, :, 2] cat_image = np.zeros((2448,2448), dtype=np.uint8) cat_image[image == 3] = 0 # (Cyan: 011) Urban land cat_image[image == 6] = 1 # (Yellow: 110) Agriculture land cat_image[image == 5] = 2 # (Purple: 101) Rangeland cat_image[image == 2] = 3 # (Green: 010) Forest land cat_image[image == 1] = 4 # (Blue: 001) Water cat_image[image == 7] = 5 # (White: 111) Barren land cat_image[image == 0] = 6 # (Black: 000) Unknown # scipy.misc.imsave(output_path, cat_image) imageio.imsave(output_path, cat_image) pass
Example #8
Source File: request_model.py From Deep-Learning-Tinder with MIT License | 6 votes |
def call_model(image, api_host='', model_id=''): tmp_filename = str(uuid.uuid4()) + '.png' imageio.imsave(tmp_filename, image) path = '/models/images/classification/classify_one.json' files = {'image_file': open(tmp_filename, 'rb')} try: r = post(api_host + path, files=files, params={'job_id': model_id}) finally: os.remove(tmp_filename) time.sleep(2) # wait 2 seconds. result = r.json() if result.get('error'): raise Exception(result.get('error').get('description')) for res_element in result['predictions']: if 'LIKE' in res_element[0]: print(result) return res_element[1] return 0.0
Example #9
Source File: io.py From napari with BSD 3-Clause "New" or "Revised" License | 6 votes |
def imsave(filename: str, data: np.ndarray): """Custom implementation of imsave to avoid skimage dependency. Parameters ---------- filename : string The path to write the file to. data : np.ndarray The image data. """ ext = os.path.splitext(filename)[1] if ext in [".tif", ".tiff"]: import tifffile tifffile.imsave(filename, data) else: import imageio imageio.imsave(filename, data)
Example #10
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #11
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #12
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #13
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #14
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #15
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #16
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #17
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #18
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #19
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #20
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #21
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #22
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #23
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #24
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #25
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #26
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #27
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #28
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #29
Source File: utility.py From U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation with MIT License | 5 votes |
def save_image_to_path(img, image_name, path): # import ipdb as pdb; pdb.set_trace() if not os.path.exists(path): print ("Path {0} does not exist".format(path)) try: os.mkdir(path) except OSError: print ("Creation of the directory {0} failed".format(path)) else: print ("Successfully created the directory {0}".format(path)) path = path+image_name img = np.asarray( img, dtype="uint8" ) imageio.imsave(path, img, "PNG")
Example #30
Source File: image.py From catalyst with Apache License 2.0 | 5 votes |
def imsave(**kwargs): """ ``imwrite(uri, im, format=None, **kwargs)`` Write an image to the specified file. Alias for ``imageio.imsave``. Args: **kwargs: parameters for ``imageio.imsave`` Returns: image save result """ return imageio.imsave(**kwargs)