Commit 7b25dd2
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- packages/bigframes
- bigframes
- blob
- operations
- notebooks/experimental
- tests/system/large/blob
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -108,6 +108,38 @@ def udf(self): | |||
| 108 | 108 | return self._session.read_gbq_function(udf_name) | |
| 109 | 109 | ||
| 110 | 110 | ||
| 111 | + def exif_func(src_obj_ref_rt: str) -> str: | ||
| 112 | + import io | ||
| 113 | + import json | ||
| 114 | + | ||
| 115 | + from PIL import ExifTags, Image | ||
| 116 | + import requests | ||
| 117 | + from requests import adapters | ||
| 118 | + | ||
| 119 | + session = requests.Session() | ||
| 120 | + session.mount("https://", adapters.HTTPAdapter(max_retries=3)) | ||
| 121 | + | ||
| 122 | + src_obj_ref_rt_json = json.loads(src_obj_ref_rt) | ||
| 123 | + | ||
| 124 | + src_url = src_obj_ref_rt_json["access_urls"]["read_url"] | ||
| 125 | + | ||
| 126 | + response = session.get(src_url, timeout=30) | ||
| 127 | + bts = response.content | ||
| 128 | + | ||
| 129 | + image = Image.open(io.BytesIO(bts)) | ||
| 130 | + exif_data = image.getexif() | ||
| 131 | + exif_dict = {} | ||
| 132 | + if exif_data: | ||
| 133 | + for tag, value in exif_data.items(): | ||
| 134 | + tag_name = ExifTags.TAGS.get(tag, tag) | ||
| 135 | + exif_dict[tag_name] = value | ||
| 136 | + | ||
| 137 | + return json.dumps(exif_dict) | ||
| 138 | + | ||
| 139 | + | ||
| 140 | + exif_func_def = FunctionDef(exif_func, ["pillow", "requests"]) | ||
| 141 | + | ||
| 142 | + | ||
| 111 | 143 | # Blur images. Takes ObjectRefRuntime as JSON string. Outputs ObjectRefRuntime JSON string. | |
| 112 | 144 | def image_blur_func( | |
| 113 | 145 | src_obj_ref_rt: str, dst_obj_ref_rt: str, ksize_x: int, ksize_y: int, ext: str | |
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -300,6 +300,46 @@ def get_runtime_json_str( | |||
| 300 | 300 | runtime = self._get_runtime(mode=mode, with_metadata=with_metadata) | |
| 301 | 301 | return runtime._apply_unary_op(ops.ToJSONString()) | |
| 302 | 302 | ||
| 303 | + def exif( | ||
| 304 | + self, | ||
| 305 | + *, | ||
| 306 | + connection: Optional[str] = None, | ||
| 307 | + max_batching_rows: int = 8192, | ||
| 308 | + container_cpu: Union[float, int] = 0.33, | ||
| 309 | + container_memory: str = "512Mi", | ||
| 310 | + ) -> bigframes.series.Series: | ||
| 311 | + """Extract EXIF data. Now only support image types. | ||
| 312 | + | ||
| 313 | + Args: | ||
| 314 | + connection (str or None, default None): BQ connection used for function internet transactions, and the output blob if "dst" is str. If None, uses default connection of the session. | ||
| 315 | + max_batching_rows (int, default 8,192): Max number of rows per batch send to cloud run to execute the function. | ||
| 316 | + container_cpu (int or float, default 0.33): number of container CPUs. Possible values are [0.33, 8]. Floats larger than 1 are cast to intergers. | ||
| 317 | + container_memory (str, default "512Mi"): container memory size. String of the format <number><unit>. Possible values are from 512Mi to 32Gi. | ||
| 318 | + | ||
| 319 | + Returns: | ||
| 320 | + bigframes.series.Series: JSON series of key-value pairs. | ||
| 321 | + """ | ||
| 322 | + | ||
| 323 | + import bigframes.bigquery as bbq | ||
| 324 | + import bigframes.blob._functions as blob_func | ||
| 325 | + | ||
| 326 | + connection = self._resolve_connection(connection) | ||
| 327 | + df = self.get_runtime_json_str(mode="R").to_frame() | ||
| 328 | + | ||
| 329 | + exif_udf = blob_func.TransformFunction( | ||
| 330 | + blob_func.exif_func_def, | ||
| 331 | + session=self._block.session, | ||
| 332 | + connection=connection, | ||
| 333 | + max_batching_rows=max_batching_rows, | ||
| 334 | + container_cpu=container_cpu, | ||
| 335 | + container_memory=container_memory, | ||
| 336 | + ).udf() | ||
| 337 | + | ||
| 338 | + res = self._df_apply_udf(df, exif_udf) | ||
| 339 | + res = bbq.parse_json(res) | ||
| 340 | + | ||
| 341 | + return res | ||
| 342 | + | ||
| 303 | 343 | def image_blur( | |
| 304 | 344 | self, | |
| 305 | 345 | ksize: tuple[int, int], | |
Lines changed: 1 addition & 1 deletion
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -106,7 +106,7 @@ | |||
| 106 | 106 | }, | |
| 107 | 107 | "source": [ | |
| 108 | 108 | "### 1. Create Multimodal DataFrame\n", | |
| 109 | - "There are several ways to create Multimodal DataFrame. The easiest way is from the wiledcard paths." | ||
| 109 | + "There are several ways to create Multimodal DataFrame. The easiest way is from the wildcard paths." | ||
| 110 | 110 | ] | |
| 111 | 111 | }, | |
| 112 | 112 | { | |
Lines changed: 24 additions & 0 deletions
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
@@ -51,6 +51,30 @@ def images_output_uris(images_output_folder: str) -> list[str]: | |||
| 51 | 51 | ] | |
| 52 | 52 | ||
| 53 | 53 | ||
| 54 | + def test_blob_exif( | ||
| 55 | + bq_connection: str, | ||
| 56 | + test_session: bigframes.Session, | ||
| 57 | + ): | ||
| 58 | + exif_image_df = test_session.from_glob_path( | ||
| 59 | + "gs://bigframes_blob_test/images_exif/*", | ||
| 60 | + name="blob_col", | ||
| 61 | + connection=bq_connection, | ||
| 62 | + ) | ||
| 63 | + | ||
| 64 | + actual = exif_image_df["blob_col"].blob.exif(connection=bq_connection) | ||
| 65 | + expected = bpd.Series( | ||
| 66 | + ['{"ExifOffset": 47, "Make": "MyCamera"}'], | ||
| 67 | + session=test_session, | ||
| 68 | + dtype=dtypes.JSON_DTYPE, | ||
| 69 | + ) | ||
| 70 | + pd.testing.assert_series_equal( | ||
| 71 | + actual.to_pandas(), | ||
| 72 | + expected.to_pandas(), | ||
| 73 | + check_dtype=False, | ||
| 74 | + check_index_type=False, | ||
| 75 | + ) | ||
| 76 | + | ||
| 77 | + | ||
| 54 | 78 | def test_blob_image_blur_to_series( | |
| 55 | 79 | images_mm_df: bpd.DataFrame, | |
| 56 | 80 | bq_connection: str, | |
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