add flickr search

3 files changed, 251 insertions, 0 deletions

diff --git a/megapixels/commands/search/flickr.py b/megapixels/commands/search/flickr.py
new file mode 100644
index 00000000..ef3515bf
--- /dev/null
+++ b/megapixels/commands/search/flickr.py
@@ -0,0 +1,71 @@
+"""
+# Examples:
+-q https://farm2.staticflickr.com/1252/1366994858_d4a2b377cc_o.jpg
+-q 48876008@N05
+-q 1366994858
+"""
+
+import click
+
+# datasets
+dataset_keys = ['pipa', 'megaface', 'helen', 'ibm_dif', 'adience', 'who_goes_there', 'vgg_face']
+
+@click.command()
+@click.option('-q', '--query', 'opt_query', type=str, required=True,
+  help='Photo URL, photo id, or NSID')
+@click.option('-o', '--output', 'opt_fp_out', required=True,
+  help='Output file CSV')
+@click.pass_context
+def cli(ctx, opt_query, opt_fp_out):
+  """Locate image by Flickr identifier"""
+
+  import sys
+  from os.path import join
+  from glob import glob
+  from pathlib import Path
+  import time
+
+  import pandas as pd
+  from tqdm import tqdm
+
+  from app.utils.logger_utils import Logger
+
+  log = Logger.getLogger()
+  log.debug(f'Search query: "{opt_query}"')
+
+  fp_dataset_base = '/data_store/datasets/people/'
+
+  matches = []
+
+  if '@' in opt_query:
+    # process NSID format
+    qk = 'nsid'
+  elif 'staticflickr.com' in opt_query:
+    # process URL to photo id
+    opt_query = Path(opt_query).name.split('_')[0]
+    qk = 'photo_id'
+  else:
+    # process as photo id
+    qk = 'photo_id'
+
+  log.debug(f'Searching Flickr data using "{qk}"')
+
+  for dk in dataset_keys:
+    # read dataset metadata
+    fp_filepaths = join(fp_dataset_base, dk, f'metadata/{dk}_filepaths.csv')
+    log.debug(f'loading: {fp_filepaths}')
+    df = pd.read_csv(fp_filepaths, dtype={'photo_id': str})  
+    photo_ids = list(df[qk])
+
+    # search for match
+    if opt_query in photo_ids:
+      log.info(f'Found "{qk} = {opt_query}" id in "{dk}"')
+      df_match = df[df[qk] == opt_query]
+      records = df_match.to_dict('records')
+      for record in records:
+        record['dataset'] = dk
+        matches.append(record)
+
+  # Write file
+  log.debug(f'Found {len(matches)} matches')
+  pd.DataFrame.from_dict(matches).to_csv(opt_fp_out, index=False)
\ No newline at end of file
diff --git a/megapixels/commands/search/flickr_nsid.py b/megapixels/commands/search/flickr_nsid.py
new file mode 100644
index 00000000..d9997090
--- /dev/null
+++ b/megapixels/commands/search/flickr_nsid.py
@@ -0,0 +1,133 @@
+from os.path import join
+
+import click
+
+from app.utils.logger_utils import Logger
+
+log = Logger.getLogger()
+
+# datasets
+dataset_keys = ['pipa', 'megaface', 'helen', 'ibm_dif', 'adience', 'who_goes_there', 'vgg_face']
+
+
+@click.command()
+@click.option('-i', '--input', 'opt_fp_in', required=True,
+  help='Input file for embassies')
+@click.option('-o', '--output', 'opt_fp_out', required=True,
+  help='Output file')
+@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None),
+  help='Slice list of files')
+@click.option('-f', '--force', 'opt_force', is_flag=True,
+  help='Force overwrite')
+@click.pass_context
+def cli(ctx, opt_fp_in, opt_fp_out, opt_slice, opt_force):
+  """Cross reference"""
+  """
+  # data input example
+  first_name  last_name nsid  path_alias  url username  skip
+  Query_01    98022916@N00  range_of_light  https://www.flickr.com/photos/range_of_light/ range_of_light  
+  """
+
+  import sys
+  from os.path import join
+  from glob import glob
+  from pathlib import Path
+  import time
+
+  import pandas as pd
+  from tqdm import tqdm
+
+  log = Logger.getLogger()
+  log.info('Cross reference embassy list')
+
+  
+  fp_counts = {}
+  fp_filepaths = {}
+  fp_dataset_base = '/data_store/datasets/people/'
+
+  for dk in dataset_keys:
+    fp_counts[dk] = join(fp_dataset_base, dk, f'metadata/{dk}_counts.csv')
+    fp_filepaths[dk] = join(fp_dataset_base, dk, f'metadata/{dk}_filepaths.csv')
+
+  df_queries = pd.read_csv(opt_fp_in)
+  df_queries.fillna('', inplace=True)
+  len_orig = len(df_queries)
+  df_queries = df_queries[df_queries.skip != True]
+  log.debug(f'Skipping {len_orig - len(df_queries)} embassies')
+  
+  query_nsids = list(df_queries['nsid'])
+
+  match_items = []
+  images = []
+
+  for dataset_key, fp_dataset in tqdm(fp_counts.items()):
+    df_counts = pd.read_csv(fp_dataset)
+    log.debug(f'loading: {fp_filepaths[dataset_key]}')
+    df_filepaths = pd.read_csv(fp_filepaths[dataset_key])
+    nsids = list(df_counts['nsid'])
+    for nsid in nsids:
+      if nsid in query_nsids:
+        # add to matches, and count
+        count = df_counts[df_counts['nsid'] == nsid]['count'].values[0]
+        first_name = df_queries[df_queries['nsid'] == nsid]['first_name'].values[0]
+        last_name = df_queries[df_queries['nsid'] == nsid]['last_name'].values[0]
+        path_alias = df_queries[df_queries['nsid'] == nsid]['path_alias'].values[0]
+        page_url = f'https://flickr.com/photos/{path_alias}'
+        name = f'{first_name} {last_name}'
+        meta = df_queries[df_queries['nsid'] == nsid].iloc[0]
+
+        match_obj = {
+          'count': count,
+          'path_alias': path_alias,
+          'name': name,
+          'dataset_key': dataset_key,
+          'nsid': nsid,
+          'page_url': page_url,
+          'username': meta.username
+        }
+        match_items.append(match_obj)
+
+        # add photo ids or url
+        df_nsids = df_filepaths[df_filepaths['nsid'] == nsid]
+        nsid_records = df_nsids.to_dict('records')
+        for nsid_record in nsid_records:
+          photo_id = nsid_record.get('photo_id')
+          im_obj = {
+            'nsid': nsid,
+            'url': nsid_record.get('url'),
+            'photo_id': photo_id,
+            'dataset_key': dataset_key,
+            'path_alias': path_alias,
+            'name': name,
+            'page_url': page_url,
+            'username': meta.username,
+            'filepath': f'{photo_id}.jpg'
+          }
+          
+          images.append(im_obj)
+
+  # Save embassy matches
+  df_matches = pd.DataFrame.from_dict(match_items)
+  df_matches.to_csv(opt_fp_out, index=False)
+  total = df_matches['count'].sum()
+  
+  # Save image matches
+  df_images = pd.DataFrame.from_dict(images)
+  fp_out = opt_fp_out.replace('.csv', '_images.csv')
+  df_images.to_csv(fp_out, index=False)
+  total = len(images)
+  log.debug(f'Found {total:,} embassy images')
+
+  # save summary count per dataset
+  groups_datasets = df_matches.groupby('dataset_key')
+  summary_counts = []
+  for group_dataset, df_dataset in groups_datasets:
+    log.debug(f'{group_dataset}')
+    summary_counts.append({'dataset': group_dataset, 'images': df_dataset['count'].sum()})
+  df_dataset_counts = pd.DataFrame.from_dict(summary_counts)
+  fp_out = opt_fp_out.replace('.csv', '_counts_summary_dataset.csv')
+  df_dataset_counts.to_csv(fp_out, index=False)
+
+  
+  log.debug(f'wrote {fp_out}')
+  log.debug(f'Found {len(images):,} embassy images')  
diff --git a/megapixels/commands/search/flickr_url.py b/megapixels/commands/search/flickr_url.py
new file mode 100644
index 00000000..bc205604
--- /dev/null
+++ b/megapixels/commands/search/flickr_url.py
@@ -0,0 +1,47 @@
+"""
+# data input example
+--url https://farm2.staticflickr.com/1252/1366994858_d4a2b377cc_o.jpg
+"""
+
+import click
+
+# datasets
+dataset_keys = ['pipa', 'megaface', 'helen', 'ibm_dif', 'adience', 'who_goes_there', 'vgg_face']
+#dataset_keys = ['pipa']
+
+@click.command()
+@click.option('-u', '--url', 'opt_url', required=True,
+  help='Photo URL')
+@click.option('-o', '--output', 'opt_fp_out',
+  help='Output file CSV')
+@click.pass_context
+def cli(ctx, opt_url, opt_fp_out):
+  """Locate image by URL"""
+
+  import sys
+  from os.path import join
+  from glob import glob
+  from pathlib import Path
+  import time
+
+  import pandas as pd
+  from tqdm import tqdm
+
+  from app.utils.logger_utils import Logger
+
+  log = Logger.getLogger()
+
+  fp_dataset_base = '/data_store/datasets/people/'
+
+  matches = []
+
+  for dk in dataset_keys:
+    
+    fp_filepaths = join(fp_dataset_base, dk, f'metadata/{dk}_filepaths.csv')
+    log.debug(f'loading: {fp_filepaths}')
+    df = pd.read_csv(fp_filepaths)
+    urls = list(df['url'])
+    if opt_url in urls:
+      log.info(f'Found image in {dk}')
+      matches.append(dk)
+