BUG: uint8 silently converted to int8 during dataframe creation
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [ ] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
# !pip install -U pandas
import pandas as pd
import numpy as np

# Create arbitrary 3-channel 8-bit image
data = np.random.randint(0, 256, size=(50,50, 3), dtype='uint8')

# Replicate this image and treat each image as a row of pixel features
rows = [data.reshape(-1)]*2
assert all(r.dtype == np.uint8 for r in rows)

print(pd.DataFrame(rows).dtypes)
# int8???

print(pd.DataFrame(np.vstack(rows)).dtypes)
# uint8 (expected)
```


### Issue Description

Apologies if this issue already exists -- type-related issues are hard for me to navigate in github since there are too many to easily parse.

`uint8` subarray dtypes are  silently converted to `int8` when constructing a dataframe from lists.

I tried testing on master but Windows has a build error for me (stack trace below),
<details>

```
building 'pandas._libs.algos' extension
  error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
  ----------------------------------------
  ERROR: Failed building wheel for pandas
Failed to build pandas
ERROR: Could not build wheels for pandas which use PEP 517 and cannot be installed directly
```

</details>

### Expected Behavior

The dtype of each unit in each column is a `uint8`, so I would expect `uint8` resulting columns

### Installed Versions

<details>

INSTALLED VERSIONS
------------------
commit           : 73c68257545b5f8530b7044f56647bd2db92e2ba
python           : 3.9.4.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_United States.1252

pandas           : 1.3.3
numpy            : 1.19.5
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.3
setuptools       : 52.0.0.post20210125
Cython           : None
pytest           : 6.2.4
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.4.3
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.1
IPython          : 7.23.1
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.2
numexpr          : None
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.3
sqlalchemy       : 1.4.15
tables           : None
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : None
numba            : None

</details>
