diff options
| -rw-r--r-- | cli/app/commands/biggan/fetch.py | 9 | ||||
| -rw-r--r-- | cli/app/search/search_class.py | 3 | ||||
| -rw-r--r-- | cli/app/search/search_dense.py | 28 | ||||
| -rw-r--r-- | cli/app/settings/app_cfg.py | 1 | ||||
| -rw-r--r-- | cli/app/utils/cortex_utils.py | 37 |
5 files changed, 59 insertions, 19 deletions
diff --git a/cli/app/commands/biggan/fetch.py b/cli/app/commands/biggan/fetch.py index 94117c9..39f503c 100644 --- a/cli/app/commands/biggan/fetch.py +++ b/cli/app/commands/biggan/fetch.py @@ -1,6 +1,7 @@ import click +import os -from app.utils.cortex_utils import fetch_cortex_folder +from app.utils.cortex_utils import fetch_cortex_folder, find_unprocessed_files @click.command('') @click.option('-i', '--folder_id', 'opt_folder_id', type=int, @@ -10,4 +11,8 @@ def cli(ctx, opt_folder_id): """ Fetch JSON from the server """ - fetch_cortex_folder(opt_folder_id) + files = fetch_cortex_folder(opt_folder_id) + unprocessed_files = find_unprocessed_files(files) + print("Unprocessed files:") + for file in unprocessed_files: + print(" - {}".format(file['name'])) diff --git a/cli/app/search/search_class.py b/cli/app/search/search_class.py index eb9ff42..eba61e8 100644 --- a/cli/app/search/search_class.py +++ b/cli/app/search/search_class.py @@ -26,7 +26,7 @@ from app.search.vector import truncated_z_sample, truncated_z_single, \ def find_nearest_vector_for_images(opt_fp_in, opt_dims, opt_steps, opt_limit, opt_video, opt_tag): sess = tf.compat.v1.Session() - + tf.reset_default_graph() generator = hub.Module('https://tfhub.dev/deepmind/biggan-512/2') if os.path.isdir(opt_fp_in): @@ -52,6 +52,7 @@ def find_nearest_vector_for_images(opt_fp_in, opt_dims, opt_steps, opt_limit, op fp_frames = find_nearest_vector(sess, generator, path, opt_dims, out_images, out_labels, out_latent, opt_steps, index) if opt_video: export_video(fp_frames) + sess.close() def find_nearest_vector(sess, generator, opt_fp_in, opt_dims, out_images, out_labels, out_latent, opt_steps, index): """ diff --git a/cli/app/search/search_dense.py b/cli/app/search/search_dense.py index 0086db5..392fa70 100644 --- a/cli/app/search/search_dense.py +++ b/cli/app/search/search_dense.py @@ -100,6 +100,8 @@ def find_dense_embedding_for_images(params): # -------------------------- # Load Graph. # -------------------------- + tf.reset_default_graph() + generator = hub.Module(str(params.generator_path)) gen_signature = 'generator' @@ -419,6 +421,9 @@ def find_dense_embedding_for_images(params): out_fns[:] = sample_fns[:NUM_IMGS_TO_PROCESS] + vector_dir = os.path.join(app_cfg.INVERSES_DIR, "vectors") + os.makedirs(vector_dir, exist_ok=True) + # Gradient descent w.r.t. generator's inputs. it = 0 out_pos = 0 @@ -485,19 +490,22 @@ def find_dense_embedding_for_images(params): # write encoding, latent to pkl file for i in range(BATCH_SIZE): out_i = out_pos + i - fn, ext = os.path.splitext(sample_fns[out_i]) - fp_out_pkl = os.path.join(app_cfg.INVERSES_DIR, fn ".pkl") - out_data = { - 'id': fn, - 'latent': out_lat[out_i], - 'encoding': out_enc[out_i], - 'label': out_labels[out_i], - } - write_pickle(out_data, fp_out_pkl) + sample_fn, ext = os.path.splitext(sample_fns[out_i]) image = Image.fromarray(images[i]) fp = BytesIO() image.save(fp, format='png') - upload_bytes_to_cortex(params.folder_id, fn, fp, 'image/png') + data = upload_bytes_to_cortex(params.folder_id, sample_fn + "-inverse.png", fp, "image/png") + if data is not None: + file_id = data['id'] + fp_out_pkl = os.path.join(vector_dir, "file_{}.pkl".format(file_id)) + out_data = { + 'id': file_id, + 'sample_fn': sample_fn, + 'label': out_labels[out_i], + 'latent': out_lat[out_i], + 'encoding': out_enc[out_i], + } + write_pickle(out_data, fp_out_pkl) out_pos += BATCH_SIZE if params.max_batches > 0 and (out_pos / BATCH_SIZE) >= params.max_batches: diff --git a/cli/app/settings/app_cfg.py b/cli/app/settings/app_cfg.py index 7e739df..bade59c 100644 --- a/cli/app/settings/app_cfg.py +++ b/cli/app/settings/app_cfg.py @@ -21,7 +21,6 @@ CLICK_GROUPS = { 'biggan': 'app/commands/biggan', 'bigbigan': 'app/commands/bigbigan', 'cortex': 'app/commands/cortex', - 'process': 'app/commands/process', } # ----------------------------------------------------------------------------- diff --git a/cli/app/utils/cortex_utils.py b/cli/app/utils/cortex_utils.py index 328b93a..8076fda 100644 --- a/cli/app/utils/cortex_utils.py +++ b/cli/app/utils/cortex_utils.py @@ -7,24 +7,49 @@ urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) from app.settings import app_cfg def api_url(path): + """Generate a base API path""" return "https://lens.neural.garden/api/{}/".format(path) def fetch_cortex_folder(opt_folder_id): + """Fetch all new, non-generated files in a Cortex folder""" rows = fetch_json(api_url('file'), folder_id=opt_folder_id) fp_out_dir = join(app_cfg.DIR_INPUTS, "cortex", str(opt_folder_id)) os.makedirs(fp_out_dir, exist_ok=True) for row in rows: if row['generated'] == 0 and row['processed'] != 1: fn, ext = os.path.splitext(row['name']) - fp_out_image = join(fp_out_dir, "{}{}".format(row['id'], ext)) + fp_out_image = join(fp_out_dir, row['name']) if not os.path.exists(fp_out_image): + row['path'] = fp_out_image fetch_file(row['url'], fp_out_image) + return rows + +def find_unprocessed_files(files): + """Find files that haven't been processed yet. + This is implied if no matching generated file is found. + """ + datasets = {} + unprocessed_files = [] + for file in files: + if file['generated'] == 1: + fn, ext = os.path.splitext(file['name']) + dataset = fn.split('-')[0] + datasets[dataset] = file['id'] + for file in files: + if file['generated'] == 0 and file['processed'] != 1: + fn, ext = os.path.splitext(file['name']) + dataset = fn.split('-')[0] + if dataset not in datasets: + unprocessed_files.append(file) + return unprocessed_files def fetch_json(url, **kwargs): + """HTTP GET some JSON""" resp = requests.get(url, params=kwargs, verify=False, timeout=10) return None if resp.status_code != 200 else resp.json() def fetch_file(url, fn, **kwargs): + """HTTP GET a binary file and write it to disk""" print("Fetch {} => {}".format(url, fn)) try: resp = requests.get(url, params=kwargs, verify=False, timeout=10) @@ -41,6 +66,7 @@ def fetch_file(url, fn, **kwargs): return size def upload_fp_to_cortex(opt_folder_id, fp): + """Upload a open file/BytesIO object""" files = { 'file': fp } @@ -52,13 +78,14 @@ def upload_fp_to_cortex(opt_folder_id, fp): 'datatype': 'image', } url = os.path.join(api_url('folder'), opt_folder_id, 'upload/') - print(url) r = requests.post(url, files=files, data=data) - print(r.json()) + return None if resp.status_code != 200 else resp.json() def upload_bytes_to_cortex(opt_folder_id, fn, fp, mimetype): - upload_fp_to_cortex(opt_folder_id, (fn, fp.getvalue(), mimetype,)) + """Upload a BytesIO object""" + return upload_fp_to_cortex(opt_folder_id, (fn, fp.getvalue(), mimetype,)) def upload_file_to_cortex(opt_folder_id, fn): + """Upload a file from disk""" with open(fn, 'rb') as fp: - upload_fp_to_cortex(opt_folder_id, fp) + return upload_fp_to_cortex(opt_folder_id, fp) |